Overview

Dataset statistics

Number of variables50
Number of observations1091
Missing cells20
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory426.3 KiB
Average record size in memory400.1 B

Variable types

Numeric4
Categorical46

Warnings

COGNITIVE EXAM 120-161: (160) SUBTRACTING SEVENS has 17 (1.6%) missing values Missing
OPTIMA DIAGNOSES V 2010: DIAGNOSTIC CODE is highly skewed (γ1 = 33.01098161) Skewed
df_index has unique values Unique
OPTIMA DIAGNOSES V 2010: DIAGNOSTIC CODE has 52 (4.8%) zeros Zeros
COGNITIVE EXAM 120-161: (160) SUBTRACTING SEVENS has 85 (7.8%) zeros Zeros

Reproduction

Analysis started2021-03-31 14:23:24.868037
Analysis finished2021-03-31 14:23:41.369682
Duration16.5 seconds
Software versionpandas-profiling v2.11.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct1091
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4554.260312
Minimum113
Maximum9581
Zeros0
Zeros (%)0.0%
Memory size8.6 KiB
2021-03-31T16:23:41.453947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum113
5-th percentile319
Q11785
median4051
Q37520.5
95-th percentile9399.5
Maximum9581
Range9468
Interquartile range (IQR)5735.5

Descriptive statistics

Standard deviation3061.49379
Coefficient of variation (CV)0.6722263507
Kurtosis-1.276745682
Mean4554.260312
Median Absolute Deviation (MAD)2659
Skewness0.2319043831
Sum4968698
Variance9372744.224
MonotocityStrictly increasing
2021-03-31T16:23:41.578020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61431
 
0.1%
6691
 
0.1%
47581
 
0.1%
6631
 
0.1%
47601
 
0.1%
6651
 
0.1%
47621
 
0.1%
6671
 
0.1%
6711
 
0.1%
94311
 
0.1%
Other values (1081)1081
99.1%
ValueCountFrequency (%)
1131
0.1%
1141
0.1%
1161
0.1%
1171
0.1%
1181
0.1%
ValueCountFrequency (%)
95811
0.1%
95801
0.1%
95791
0.1%
95771
0.1%
95721
0.1%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
582 
Poor
256 
Not asked
239 
Incorrect
 
14

Length

Max length9
Median length7
Mean length6.759853346
Min length4

Characters and Unicode

Total characters7375
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct582
53.3%
Poor256
23.5%
Not asked239
21.9%
Incorrect14
 
1.3%
2021-03-31T16:23:41.855990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:41.928583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct582
43.8%
poor256
19.2%
not239
18.0%
asked239
18.0%
incorrect14
 
1.1%

Most occurring characters

ValueCountFrequency (%)
r1448
19.6%
o1347
18.3%
t835
11.3%
e835
11.3%
c610
8.3%
C582
7.9%
P256
 
3.5%
N239
 
3.2%
239
 
3.2%
a239
 
3.2%
Other values (5)745
10.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6045
82.0%
Uppercase Letter1091
 
14.8%
Space Separator239
 
3.2%

Most frequent character per category

ValueCountFrequency (%)
r1448
24.0%
o1347
22.3%
t835
13.8%
e835
13.8%
c610
10.1%
a239
 
4.0%
s239
 
4.0%
k239
 
4.0%
d239
 
4.0%
n14
 
0.2%
ValueCountFrequency (%)
C582
53.3%
P256
23.5%
N239
21.9%
I14
 
1.3%
ValueCountFrequency (%)
239
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7136
96.8%
Common239
 
3.2%

Most frequent character per script

ValueCountFrequency (%)
r1448
20.3%
o1347
18.9%
t835
11.7%
e835
11.7%
c610
8.5%
C582
8.2%
P256
 
3.6%
N239
 
3.3%
a239
 
3.3%
s239
 
3.3%
Other values (4)506
 
7.1%
ValueCountFrequency (%)
239
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII7375
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1448
19.6%
o1347
18.3%
t835
11.3%
e835
11.3%
c610
8.3%
C582
7.9%
P256
 
3.5%
N239
 
3.2%
239
 
3.2%
a239
 
3.2%
Other values (5)745
10.1%
Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
0.0
412 
3.0
256 
2.0
223 
1.0
198 
9.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3273
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row2.0
3rd row1.0
4th row2.0
5th row2.0
ValueCountFrequency (%)
0.0412
37.8%
3.0256
23.5%
2.0223
20.4%
1.0198
18.1%
9.02
 
0.2%
2021-03-31T16:23:42.136863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:42.198468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0412
37.8%
3.0256
23.5%
2.0223
20.4%
1.0198
18.1%
9.02
 
0.2%

Most occurring characters

ValueCountFrequency (%)
01503
45.9%
.1091
33.3%
3256
 
7.8%
2223
 
6.8%
1198
 
6.0%
92
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2182
66.7%
Other Punctuation1091
33.3%

Most frequent character per category

ValueCountFrequency (%)
01503
68.9%
3256
 
11.7%
2223
 
10.2%
1198
 
9.1%
92
 
0.1%
ValueCountFrequency (%)
.1091
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3273
100.0%

Most frequent character per script

ValueCountFrequency (%)
01503
45.9%
.1091
33.3%
3256
 
7.8%
2223
 
6.8%
1198
 
6.0%
92
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII3273
100.0%

Most frequent character per block

ValueCountFrequency (%)
01503
45.9%
.1091
33.3%
3256
 
7.8%
2223
 
6.8%
1198
 
6.0%
92
 
0.1%
Distinct4
Distinct (%)0.4%
Missing1
Missing (%)0.1%
Memory size8.6 KiB
Not asked
877 
Right
180 
Left
 
29
Ambidextrous
 
4

Length

Max length12
Median length9
Mean length8.217431193
Min length4

Characters and Unicode

Total characters8957
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowNot asked
3rd rowNot asked
4th rowNot asked
5th rowNot asked
ValueCountFrequency (%)
Not asked877
80.4%
Right180
 
16.5%
Left29
 
2.7%
Ambidextrous4
 
0.4%
(Missing)1
 
0.1%
2021-03-31T16:23:42.409993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:42.475855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
not877
44.6%
asked877
44.6%
right180
 
9.2%
left29
 
1.5%
ambidextrous4
 
0.2%

Most occurring characters

ValueCountFrequency (%)
t1090
12.2%
e910
10.2%
o881
9.8%
s881
9.8%
d881
9.8%
N877
9.8%
877
9.8%
a877
9.8%
k877
9.8%
i184
 
2.1%
Other values (11)622
6.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6990
78.0%
Uppercase Letter1090
 
12.2%
Space Separator877
 
9.8%

Most frequent character per category

ValueCountFrequency (%)
t1090
15.6%
e910
13.0%
o881
12.6%
s881
12.6%
d881
12.6%
a877
12.5%
k877
12.5%
i184
 
2.6%
g180
 
2.6%
h180
 
2.6%
Other values (6)49
 
0.7%
ValueCountFrequency (%)
N877
80.5%
R180
 
16.5%
L29
 
2.7%
A4
 
0.4%
ValueCountFrequency (%)
877
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8080
90.2%
Common877
 
9.8%

Most frequent character per script

ValueCountFrequency (%)
t1090
13.5%
e910
11.3%
o881
10.9%
s881
10.9%
d881
10.9%
N877
10.9%
a877
10.9%
k877
10.9%
i184
 
2.3%
R180
 
2.2%
Other values (10)442
5.5%
ValueCountFrequency (%)
877
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8957
100.0%

Most frequent character per block

ValueCountFrequency (%)
t1090
12.2%
e910
10.2%
o881
9.8%
s881
9.8%
d881
9.8%
N877
9.8%
877
9.8%
a877
9.8%
k877
9.8%
i184
 
2.1%
Other values (11)622
6.9%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
548 
Incorrect
299 
Not asked
244 

Length

Max length9
Median length7
Mean length7.995417049
Min length7

Characters and Unicode

Total characters8723
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct548
50.2%
Incorrect299
27.4%
Not asked244
22.4%
2021-03-31T16:23:42.663208image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:43.657619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct548
41.0%
incorrect299
22.4%
not244
18.3%
asked244
18.3%

Most occurring characters

ValueCountFrequency (%)
r1694
19.4%
c1146
13.1%
o1091
12.5%
t1091
12.5%
e1091
12.5%
C548
 
6.3%
I299
 
3.4%
n299
 
3.4%
N244
 
2.8%
244
 
2.8%
Other values (4)976
11.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7388
84.7%
Uppercase Letter1091
 
12.5%
Space Separator244
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1694
22.9%
c1146
15.5%
o1091
14.8%
t1091
14.8%
e1091
14.8%
n299
 
4.0%
a244
 
3.3%
s244
 
3.3%
k244
 
3.3%
d244
 
3.3%
ValueCountFrequency (%)
C548
50.2%
I299
27.4%
N244
22.4%
ValueCountFrequency (%)
244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8479
97.2%
Common244
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1694
20.0%
c1146
13.5%
o1091
12.9%
t1091
12.9%
e1091
12.9%
C548
 
6.5%
I299
 
3.5%
n299
 
3.5%
N244
 
2.9%
a244
 
2.9%
Other values (3)732
8.6%
ValueCountFrequency (%)
244
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8723
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1694
19.4%
c1146
13.1%
o1091
12.5%
t1091
12.5%
e1091
12.5%
C548
 
6.3%
I299
 
3.4%
n299
 
3.4%
N244
 
2.8%
244
 
2.8%
Other values (4)976
11.2%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
710 
Not asked
238 
Correct
143 

Length

Max length9
Median length9
Mean length8.737855179
Min length7

Characters and Unicode

Total characters9533
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowIncorrect
3rd rowNot asked
4th rowNot asked
5th rowIncorrect
ValueCountFrequency (%)
Incorrect710
65.1%
Not asked238
 
21.8%
Correct143
 
13.1%
2021-03-31T16:23:43.831214image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:43.896925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect710
53.4%
not238
 
17.9%
asked238
 
17.9%
correct143
 
10.8%

Most occurring characters

ValueCountFrequency (%)
r1706
17.9%
c1563
16.4%
o1091
11.4%
t1091
11.4%
e1091
11.4%
I710
7.4%
n710
7.4%
N238
 
2.5%
238
 
2.5%
a238
 
2.5%
Other values (4)857
9.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8204
86.1%
Uppercase Letter1091
 
11.4%
Space Separator238
 
2.5%

Most frequent character per category

ValueCountFrequency (%)
r1706
20.8%
c1563
19.1%
o1091
13.3%
t1091
13.3%
e1091
13.3%
n710
8.7%
a238
 
2.9%
s238
 
2.9%
k238
 
2.9%
d238
 
2.9%
ValueCountFrequency (%)
I710
65.1%
N238
 
21.8%
C143
 
13.1%
ValueCountFrequency (%)
238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9295
97.5%
Common238
 
2.5%

Most frequent character per script

ValueCountFrequency (%)
r1706
18.4%
c1563
16.8%
o1091
11.7%
t1091
11.7%
e1091
11.7%
I710
7.6%
n710
7.6%
N238
 
2.6%
a238
 
2.6%
s238
 
2.6%
Other values (3)619
 
6.7%
ValueCountFrequency (%)
238
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9533
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1706
17.9%
c1563
16.4%
o1091
11.4%
t1091
11.4%
e1091
11.4%
I710
7.4%
n710
7.4%
N238
 
2.5%
238
 
2.5%
a238
 
2.5%
Other values (4)857
9.0%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
608 
Incorrect
244 
Not asked
239 

Length

Max length9
Median length7
Mean length7.885426214
Min length7

Characters and Unicode

Total characters8603
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct608
55.7%
Incorrect244
22.4%
Not asked239
 
21.9%
2021-03-31T16:23:44.121738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:44.192440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct608
45.7%
incorrect244
18.3%
not239
 
18.0%
asked239
 
18.0%

Most occurring characters

ValueCountFrequency (%)
r1704
19.8%
c1096
12.7%
o1091
12.7%
t1091
12.7%
e1091
12.7%
C608
 
7.1%
I244
 
2.8%
n244
 
2.8%
N239
 
2.8%
239
 
2.8%
Other values (4)956
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7273
84.5%
Uppercase Letter1091
 
12.7%
Space Separator239
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1704
23.4%
c1096
15.1%
o1091
15.0%
t1091
15.0%
e1091
15.0%
n244
 
3.4%
a239
 
3.3%
s239
 
3.3%
k239
 
3.3%
d239
 
3.3%
ValueCountFrequency (%)
C608
55.7%
I244
22.4%
N239
 
21.9%
ValueCountFrequency (%)
239
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8364
97.2%
Common239
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1704
20.4%
c1096
13.1%
o1091
13.0%
t1091
13.0%
e1091
13.0%
C608
 
7.3%
I244
 
2.9%
n244
 
2.9%
N239
 
2.9%
a239
 
2.9%
Other values (3)717
8.6%
ValueCountFrequency (%)
239
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8603
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1704
19.8%
c1096
12.7%
o1091
12.7%
t1091
12.7%
e1091
12.7%
C608
 
7.1%
I244
 
2.8%
n244
 
2.8%
N239
 
2.8%
239
 
2.8%
Other values (4)956
11.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
570 
Incorrect
282 
Not asked
239 

Length

Max length9
Median length7
Mean length7.955087076
Min length7

Characters and Unicode

Total characters8679
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct570
52.2%
Incorrect282
25.8%
Not asked239
21.9%
2021-03-31T16:23:44.378440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:44.451054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct570
42.9%
incorrect282
21.2%
not239
18.0%
asked239
18.0%

Most occurring characters

ValueCountFrequency (%)
r1704
19.6%
c1134
13.1%
o1091
12.6%
t1091
12.6%
e1091
12.6%
C570
 
6.6%
I282
 
3.2%
n282
 
3.2%
N239
 
2.8%
239
 
2.8%
Other values (4)956
11.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7349
84.7%
Uppercase Letter1091
 
12.6%
Space Separator239
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1704
23.2%
c1134
15.4%
o1091
14.8%
t1091
14.8%
e1091
14.8%
n282
 
3.8%
a239
 
3.3%
s239
 
3.3%
k239
 
3.3%
d239
 
3.3%
ValueCountFrequency (%)
C570
52.2%
I282
25.8%
N239
21.9%
ValueCountFrequency (%)
239
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8440
97.2%
Common239
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1704
20.2%
c1134
13.4%
o1091
12.9%
t1091
12.9%
e1091
12.9%
C570
 
6.8%
I282
 
3.3%
n282
 
3.3%
N239
 
2.8%
a239
 
2.8%
Other values (3)717
8.5%
ValueCountFrequency (%)
239
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8679
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1704
19.6%
c1134
13.1%
o1091
12.6%
t1091
12.6%
e1091
12.6%
C570
 
6.6%
I282
 
3.2%
n282
 
3.2%
N239
 
2.8%
239
 
2.8%
Other values (4)956
11.0%

Age At Episode
Real number (ℝ≥0)

Distinct46
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.26214482
Minimum51
Maximum96
Zeros0
Zeros (%)0.0%
Memory size8.6 KiB
2021-03-31T16:23:44.540374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum51
5-th percentile61
Q171
median78
Q384
95-th percentile90
Maximum96
Range45
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.7189042
Coefficient of variation (CV)0.1128483324
Kurtosis-0.2031759013
Mean77.26214482
Median Absolute Deviation (MAD)6
Skewness-0.4804473532
Sum84293
Variance76.01929044
MonotocityNot monotonic
2021-03-31T16:23:44.663481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
8556
 
5.1%
8253
 
4.9%
7852
 
4.8%
7949
 
4.5%
7648
 
4.4%
8048
 
4.4%
7747
 
4.3%
8445
 
4.1%
8643
 
3.9%
8340
 
3.7%
Other values (36)610
55.9%
ValueCountFrequency (%)
512
 
0.2%
522
 
0.2%
531
 
0.1%
542
 
0.2%
555
0.5%
ValueCountFrequency (%)
961
 
0.1%
951
 
0.1%
946
0.5%
9311
1.0%
9211
1.0%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
535 
Incorrect
315 
Not asked
241 

Length

Max length9
Median length9
Mean length8.019248396
Min length7

Characters and Unicode

Total characters8749
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct535
49.0%
Incorrect315
28.9%
Not asked241
22.1%
2021-03-31T16:23:44.871313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:44.939613image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct535
40.2%
incorrect315
23.6%
not241
18.1%
asked241
18.1%

Most occurring characters

ValueCountFrequency (%)
r1700
19.4%
c1165
13.3%
o1091
12.5%
t1091
12.5%
e1091
12.5%
C535
 
6.1%
I315
 
3.6%
n315
 
3.6%
N241
 
2.8%
241
 
2.8%
Other values (4)964
11.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7417
84.8%
Uppercase Letter1091
 
12.5%
Space Separator241
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1700
22.9%
c1165
15.7%
o1091
14.7%
t1091
14.7%
e1091
14.7%
n315
 
4.2%
a241
 
3.2%
s241
 
3.2%
k241
 
3.2%
d241
 
3.2%
ValueCountFrequency (%)
C535
49.0%
I315
28.9%
N241
22.1%
ValueCountFrequency (%)
241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8508
97.2%
Common241
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1700
20.0%
c1165
13.7%
o1091
12.8%
t1091
12.8%
e1091
12.8%
C535
 
6.3%
I315
 
3.7%
n315
 
3.7%
N241
 
2.8%
a241
 
2.8%
Other values (3)723
8.5%
ValueCountFrequency (%)
241
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8749
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1700
19.4%
c1165
13.3%
o1091
12.5%
t1091
12.5%
e1091
12.5%
C535
 
6.1%
I315
 
3.6%
n315
 
3.6%
N241
 
2.8%
241
 
2.8%
Other values (4)964
11.0%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
465 
Incorrect
384 
Not asked
242 

Length

Max length9
Median length9
Mean length8.147571036
Min length7

Characters and Unicode

Total characters8889
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct465
42.6%
Incorrect384
35.2%
Not asked242
22.2%
2021-03-31T16:23:45.113522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:45.206806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct465
34.9%
incorrect384
28.8%
not242
18.2%
asked242
18.2%

Most occurring characters

ValueCountFrequency (%)
r1698
19.1%
c1233
13.9%
o1091
12.3%
t1091
12.3%
e1091
12.3%
C465
 
5.2%
I384
 
4.3%
n384
 
4.3%
N242
 
2.7%
242
 
2.7%
Other values (4)968
10.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7556
85.0%
Uppercase Letter1091
 
12.3%
Space Separator242
 
2.7%

Most frequent character per category

ValueCountFrequency (%)
r1698
22.5%
c1233
16.3%
o1091
14.4%
t1091
14.4%
e1091
14.4%
n384
 
5.1%
a242
 
3.2%
s242
 
3.2%
k242
 
3.2%
d242
 
3.2%
ValueCountFrequency (%)
C465
42.6%
I384
35.2%
N242
22.2%
ValueCountFrequency (%)
242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8647
97.3%
Common242
 
2.7%

Most frequent character per script

ValueCountFrequency (%)
r1698
19.6%
c1233
14.3%
o1091
12.6%
t1091
12.6%
e1091
12.6%
C465
 
5.4%
I384
 
4.4%
n384
 
4.4%
N242
 
2.8%
a242
 
2.8%
Other values (3)726
8.4%
ValueCountFrequency (%)
242
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8889
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1698
19.1%
c1233
13.9%
o1091
12.3%
t1091
12.3%
e1091
12.3%
C465
 
5.2%
I384
 
4.3%
n384
 
4.3%
N242
 
2.7%
242
 
2.7%
Other values (4)968
10.9%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
652 
Not asked
243 
Partly correct
150 
Incorrect
 
46

Length

Max length14
Median length7
Mean length8.492208983
Min length7

Characters and Unicode

Total characters9265
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct652
59.8%
Not asked243
 
22.3%
Partly correct150
 
13.7%
Incorrect46
 
4.2%
2021-03-31T16:23:45.384894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:45.456067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct802
54.0%
not243
 
16.4%
asked243
 
16.4%
partly150
 
10.1%
incorrect46
 
3.1%

Most occurring characters

ValueCountFrequency (%)
r1846
19.9%
t1241
13.4%
o1091
11.8%
e1091
11.8%
c1044
11.3%
C652
 
7.0%
393
 
4.2%
a393
 
4.2%
N243
 
2.6%
s243
 
2.6%
Other values (7)1028
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7781
84.0%
Uppercase Letter1091
 
11.8%
Space Separator393
 
4.2%

Most frequent character per category

ValueCountFrequency (%)
r1846
23.7%
t1241
15.9%
o1091
14.0%
e1091
14.0%
c1044
13.4%
a393
 
5.1%
s243
 
3.1%
k243
 
3.1%
d243
 
3.1%
l150
 
1.9%
Other values (2)196
 
2.5%
ValueCountFrequency (%)
C652
59.8%
N243
 
22.3%
P150
 
13.7%
I46
 
4.2%
ValueCountFrequency (%)
393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8872
95.8%
Common393
 
4.2%

Most frequent character per script

ValueCountFrequency (%)
r1846
20.8%
t1241
14.0%
o1091
12.3%
e1091
12.3%
c1044
11.8%
C652
 
7.3%
a393
 
4.4%
N243
 
2.7%
s243
 
2.7%
k243
 
2.7%
Other values (6)785
8.8%
ValueCountFrequency (%)
393
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9265
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1846
19.9%
t1241
13.4%
o1091
11.8%
e1091
11.8%
c1044
11.3%
C652
 
7.0%
393
 
4.2%
a393
 
4.2%
N243
 
2.6%
s243
 
2.6%
Other values (7)1028
11.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
664 
Not asked
240 
Incorrect
187 

Length

Max length9
Median length7
Mean length7.782768103
Min length7

Characters and Unicode

Total characters8491
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct664
60.9%
Not asked240
 
22.0%
Incorrect187
 
17.1%
2021-03-31T16:23:45.652978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:45.724970image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct664
49.9%
not240
 
18.0%
asked240
 
18.0%
incorrect187
 
14.0%

Most occurring characters

ValueCountFrequency (%)
r1702
20.0%
o1091
12.8%
t1091
12.8%
e1091
12.8%
c1038
12.2%
C664
 
7.8%
N240
 
2.8%
240
 
2.8%
a240
 
2.8%
s240
 
2.8%
Other values (4)854
10.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7160
84.3%
Uppercase Letter1091
 
12.8%
Space Separator240
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1702
23.8%
o1091
15.2%
t1091
15.2%
e1091
15.2%
c1038
14.5%
a240
 
3.4%
s240
 
3.4%
k240
 
3.4%
d240
 
3.4%
n187
 
2.6%
ValueCountFrequency (%)
C664
60.9%
N240
 
22.0%
I187
 
17.1%
ValueCountFrequency (%)
240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8251
97.2%
Common240
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1702
20.6%
o1091
13.2%
t1091
13.2%
e1091
13.2%
c1038
12.6%
C664
 
8.0%
N240
 
2.9%
a240
 
2.9%
s240
 
2.9%
k240
 
2.9%
Other values (3)614
 
7.4%
ValueCountFrequency (%)
240
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8491
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1702
20.0%
o1091
12.8%
t1091
12.8%
e1091
12.8%
c1038
12.2%
C664
 
7.8%
N240
 
2.8%
240
 
2.8%
a240
 
2.8%
s240
 
2.8%
Other values (4)854
10.1%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Negative
537 
Possible
240 
Probable
191 
Not asked
123 

Length

Max length9
Median length8
Mean length8.112740605
Min length8

Characters and Unicode

Total characters8851
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNegative
2nd rowNegative
3rd rowNegative
4th rowNegative
5th rowNegative
ValueCountFrequency (%)
Negative537
49.2%
Possible240
22.0%
Probable191
 
17.5%
Not asked123
 
11.3%
2021-03-31T16:23:45.891312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:45.954612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
negative537
44.2%
possible240
19.8%
probable191
 
15.7%
not123
 
10.1%
asked123
 
10.1%

Most occurring characters

ValueCountFrequency (%)
e1628
18.4%
a851
9.6%
i777
8.8%
N660
7.5%
t660
7.5%
b622
 
7.0%
s603
 
6.8%
o554
 
6.3%
g537
 
6.1%
v537
 
6.1%
Other values (6)1422
16.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7637
86.3%
Uppercase Letter1091
 
12.3%
Space Separator123
 
1.4%

Most frequent character per category

ValueCountFrequency (%)
e1628
21.3%
a851
11.1%
i777
10.2%
t660
8.6%
b622
 
8.1%
s603
 
7.9%
o554
 
7.3%
g537
 
7.0%
v537
 
7.0%
l431
 
5.6%
Other values (3)437
 
5.7%
ValueCountFrequency (%)
N660
60.5%
P431
39.5%
ValueCountFrequency (%)
123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8728
98.6%
Common123
 
1.4%

Most frequent character per script

ValueCountFrequency (%)
e1628
18.7%
a851
9.8%
i777
8.9%
N660
7.6%
t660
7.6%
b622
 
7.1%
s603
 
6.9%
o554
 
6.3%
g537
 
6.2%
v537
 
6.2%
Other values (5)1299
14.9%
ValueCountFrequency (%)
123
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8851
100.0%

Most frequent character per block

ValueCountFrequency (%)
e1628
18.4%
a851
9.6%
i777
8.8%
N660
7.5%
t660
7.5%
b622
 
7.0%
s603
 
6.8%
o554
 
6.3%
g537
 
6.1%
v537
 
6.1%
Other values (6)1422
16.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
No
496 
Yes
481 
Not asked
114 

Length

Max length9
Median length3
Mean length3.172318973
Min length2

Characters and Unicode

Total characters3461
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
No496
45.5%
Yes481
44.1%
Not asked114
 
10.4%
2021-03-31T16:23:46.151777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:46.218855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
no496
41.2%
yes481
39.9%
not114
 
9.5%
asked114
 
9.5%

Most occurring characters

ValueCountFrequency (%)
N610
17.6%
o610
17.6%
e595
17.2%
s595
17.2%
Y481
13.9%
t114
 
3.3%
114
 
3.3%
a114
 
3.3%
k114
 
3.3%
d114
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2256
65.2%
Uppercase Letter1091
31.5%
Space Separator114
 
3.3%

Most frequent character per category

ValueCountFrequency (%)
o610
27.0%
e595
26.4%
s595
26.4%
t114
 
5.1%
a114
 
5.1%
k114
 
5.1%
d114
 
5.1%
ValueCountFrequency (%)
N610
55.9%
Y481
44.1%
ValueCountFrequency (%)
114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3347
96.7%
Common114
 
3.3%

Most frequent character per script

ValueCountFrequency (%)
N610
18.2%
o610
18.2%
e595
17.8%
s595
17.8%
Y481
14.4%
t114
 
3.4%
a114
 
3.4%
k114
 
3.4%
d114
 
3.4%
ValueCountFrequency (%)
114
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3461
100.0%

Most frequent character per block

ValueCountFrequency (%)
N610
17.6%
o610
17.6%
e595
17.2%
s595
17.2%
Y481
13.9%
t114
 
3.3%
114
 
3.3%
a114
 
3.3%
k114
 
3.3%
d114
 
3.3%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
689 
Not asked
238 
Correct
164 

Length

Max length9
Median length9
Mean length8.699358387
Min length7

Characters and Unicode

Total characters9491
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowIncorrect
3rd rowNot asked
4th rowNot asked
5th rowIncorrect
ValueCountFrequency (%)
Incorrect689
63.2%
Not asked238
 
21.8%
Correct164
 
15.0%
2021-03-31T16:23:46.405925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:46.475602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect689
51.8%
not238
 
17.9%
asked238
 
17.9%
correct164
 
12.3%

Most occurring characters

ValueCountFrequency (%)
r1706
18.0%
c1542
16.2%
o1091
11.5%
t1091
11.5%
e1091
11.5%
I689
7.3%
n689
7.3%
N238
 
2.5%
238
 
2.5%
a238
 
2.5%
Other values (4)878
9.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8162
86.0%
Uppercase Letter1091
 
11.5%
Space Separator238
 
2.5%

Most frequent character per category

ValueCountFrequency (%)
r1706
20.9%
c1542
18.9%
o1091
13.4%
t1091
13.4%
e1091
13.4%
n689
8.4%
a238
 
2.9%
s238
 
2.9%
k238
 
2.9%
d238
 
2.9%
ValueCountFrequency (%)
I689
63.2%
N238
 
21.8%
C164
 
15.0%
ValueCountFrequency (%)
238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9253
97.5%
Common238
 
2.5%

Most frequent character per script

ValueCountFrequency (%)
r1706
18.4%
c1542
16.7%
o1091
11.8%
t1091
11.8%
e1091
11.8%
I689
7.4%
n689
7.4%
N238
 
2.6%
a238
 
2.6%
s238
 
2.6%
Other values (3)640
 
6.9%
ValueCountFrequency (%)
238
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9491
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1706
18.0%
c1542
16.2%
o1091
11.5%
t1091
11.5%
e1091
11.5%
I689
7.3%
n689
7.3%
N238
 
2.5%
238
 
2.5%
a238
 
2.5%
Other values (4)878
9.3%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
757 
Incorrect
333 
Not asked
 
1

Length

Max length9
Median length7
Mean length7.61228231
Min length7

Characters and Unicode

Total characters8305
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowCorrect
2nd rowCorrect
3rd rowCorrect
4th rowCorrect
5th rowCorrect
ValueCountFrequency (%)
Correct757
69.4%
Incorrect333
30.5%
Not asked1
 
0.1%
2021-03-31T16:23:46.660714image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:46.736240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct757
69.3%
incorrect333
30.5%
not1
 
0.1%
asked1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
r2180
26.2%
c1423
17.1%
o1091
13.1%
e1091
13.1%
t1091
13.1%
C757
 
9.1%
I333
 
4.0%
n333
 
4.0%
N1
 
< 0.1%
1
 
< 0.1%
Other values (4)4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7213
86.9%
Uppercase Letter1091
 
13.1%
Space Separator1
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
r2180
30.2%
c1423
19.7%
o1091
15.1%
e1091
15.1%
t1091
15.1%
n333
 
4.6%
a1
 
< 0.1%
s1
 
< 0.1%
k1
 
< 0.1%
d1
 
< 0.1%
ValueCountFrequency (%)
C757
69.4%
I333
30.5%
N1
 
0.1%
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8304
> 99.9%
Common1
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
r2180
26.3%
c1423
17.1%
o1091
13.1%
e1091
13.1%
t1091
13.1%
C757
 
9.1%
I333
 
4.0%
n333
 
4.0%
N1
 
< 0.1%
a1
 
< 0.1%
Other values (3)3
 
< 0.1%
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8305
100.0%

Most frequent character per block

ValueCountFrequency (%)
r2180
26.2%
c1423
17.1%
o1091
13.1%
e1091
13.1%
t1091
13.1%
C757
 
9.1%
I333
 
4.0%
n333
 
4.0%
N1
 
< 0.1%
1
 
< 0.1%
Other values (4)4
 
< 0.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
646 
Not asked
236 
Incorrect
209 

Length

Max length9
Median length7
Mean length7.815765353
Min length7

Characters and Unicode

Total characters8527
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct646
59.2%
Not asked236
 
21.6%
Incorrect209
 
19.2%
2021-03-31T16:23:46.955671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:47.067909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct646
48.7%
not236
 
17.8%
asked236
 
17.8%
incorrect209
 
15.7%

Most occurring characters

ValueCountFrequency (%)
r1710
20.1%
o1091
12.8%
t1091
12.8%
e1091
12.8%
c1064
12.5%
C646
 
7.6%
N236
 
2.8%
236
 
2.8%
a236
 
2.8%
s236
 
2.8%
Other values (4)890
10.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7200
84.4%
Uppercase Letter1091
 
12.8%
Space Separator236
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1710
23.8%
o1091
15.2%
t1091
15.2%
e1091
15.2%
c1064
14.8%
a236
 
3.3%
s236
 
3.3%
k236
 
3.3%
d236
 
3.3%
n209
 
2.9%
ValueCountFrequency (%)
C646
59.2%
N236
 
21.6%
I209
 
19.2%
ValueCountFrequency (%)
236
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8291
97.2%
Common236
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1710
20.6%
o1091
13.2%
t1091
13.2%
e1091
13.2%
c1064
12.8%
C646
 
7.8%
N236
 
2.8%
a236
 
2.8%
s236
 
2.8%
k236
 
2.8%
Other values (3)654
 
7.9%
ValueCountFrequency (%)
236
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8527
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1710
20.1%
o1091
12.8%
t1091
12.8%
e1091
12.8%
c1064
12.5%
C646
 
7.6%
N236
 
2.8%
236
 
2.8%
a236
 
2.8%
s236
 
2.8%
Other values (4)890
10.4%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
586 
Incorrect
495 
Not asked
 
10

Length

Max length9
Median length7
Mean length7.925756187
Min length7

Characters and Unicode

Total characters8647
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCorrect
2nd rowCorrect
3rd rowCorrect
4th rowCorrect
5th rowCorrect
ValueCountFrequency (%)
Correct586
53.7%
Incorrect495
45.4%
Not asked10
 
0.9%
2021-03-31T16:23:47.256017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:47.332466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct586
53.2%
incorrect495
45.0%
not10
 
0.9%
asked10
 
0.9%

Most occurring characters

ValueCountFrequency (%)
r2162
25.0%
c1576
18.2%
o1091
12.6%
e1091
12.6%
t1091
12.6%
C586
 
6.8%
I495
 
5.7%
n495
 
5.7%
N10
 
0.1%
10
 
0.1%
Other values (4)40
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7546
87.3%
Uppercase Letter1091
 
12.6%
Space Separator10
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
r2162
28.7%
c1576
20.9%
o1091
14.5%
e1091
14.5%
t1091
14.5%
n495
 
6.6%
a10
 
0.1%
s10
 
0.1%
k10
 
0.1%
d10
 
0.1%
ValueCountFrequency (%)
C586
53.7%
I495
45.4%
N10
 
0.9%
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8637
99.9%
Common10
 
0.1%

Most frequent character per script

ValueCountFrequency (%)
r2162
25.0%
c1576
18.2%
o1091
12.6%
e1091
12.6%
t1091
12.6%
C586
 
6.8%
I495
 
5.7%
n495
 
5.7%
N10
 
0.1%
a10
 
0.1%
Other values (3)30
 
0.3%
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8647
100.0%

Most frequent character per block

ValueCountFrequency (%)
r2162
25.0%
c1576
18.2%
o1091
12.6%
e1091
12.6%
t1091
12.6%
C586
 
6.8%
I495
 
5.7%
n495
 
5.7%
N10
 
0.1%
10
 
0.1%
Other values (4)40
 
0.5%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Not asked
568 
Yes
443 
No
80 

Length

Max length9
Median length9
Mean length6.050412466
Min length2

Characters and Unicode

Total characters6601
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowNot asked
3rd rowNot asked
4th rowNot asked
5th rowNot asked
ValueCountFrequency (%)
Not asked568
52.1%
Yes443
40.6%
No80
 
7.3%
2021-03-31T16:23:47.680869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:47.748312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
not568
34.2%
asked568
34.2%
yes443
26.7%
no80
 
4.8%

Most occurring characters

ValueCountFrequency (%)
s1011
15.3%
e1011
15.3%
N648
9.8%
o648
9.8%
t568
8.6%
568
8.6%
a568
8.6%
k568
8.6%
d568
8.6%
Y443
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4942
74.9%
Uppercase Letter1091
 
16.5%
Space Separator568
 
8.6%

Most frequent character per category

ValueCountFrequency (%)
s1011
20.5%
e1011
20.5%
o648
13.1%
t568
11.5%
a568
11.5%
k568
11.5%
d568
11.5%
ValueCountFrequency (%)
N648
59.4%
Y443
40.6%
ValueCountFrequency (%)
568
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6033
91.4%
Common568
 
8.6%

Most frequent character per script

ValueCountFrequency (%)
s1011
16.8%
e1011
16.8%
N648
10.7%
o648
10.7%
t568
9.4%
a568
9.4%
k568
9.4%
d568
9.4%
Y443
7.3%
ValueCountFrequency (%)
568
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6601
100.0%

Most frequent character per block

ValueCountFrequency (%)
s1011
15.3%
e1011
15.3%
N648
9.8%
o648
9.8%
t568
8.6%
568
8.6%
a568
8.6%
k568
8.6%
d568
8.6%
Y443
6.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
692 
Incorrect
396 
Not asked
 
3

Length

Max length9
Median length7
Mean length7.731439047
Min length7

Characters and Unicode

Total characters8435
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCorrect
2nd rowIncorrect
3rd rowCorrect
4th rowCorrect
5th rowCorrect
ValueCountFrequency (%)
Correct692
63.4%
Incorrect396
36.3%
Not asked3
 
0.3%
2021-03-31T16:23:47.931180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:48.005762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct692
63.3%
incorrect396
36.2%
not3
 
0.3%
asked3
 
0.3%

Most occurring characters

ValueCountFrequency (%)
r2176
25.8%
c1484
17.6%
o1091
12.9%
e1091
12.9%
t1091
12.9%
C692
 
8.2%
I396
 
4.7%
n396
 
4.7%
N3
 
< 0.1%
3
 
< 0.1%
Other values (4)12
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7341
87.0%
Uppercase Letter1091
 
12.9%
Space Separator3
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
r2176
29.6%
c1484
20.2%
o1091
14.9%
e1091
14.9%
t1091
14.9%
n396
 
5.4%
a3
 
< 0.1%
s3
 
< 0.1%
k3
 
< 0.1%
d3
 
< 0.1%
ValueCountFrequency (%)
C692
63.4%
I396
36.3%
N3
 
0.3%
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8432
> 99.9%
Common3
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
r2176
25.8%
c1484
17.6%
o1091
12.9%
e1091
12.9%
t1091
12.9%
C692
 
8.2%
I396
 
4.7%
n396
 
4.7%
N3
 
< 0.1%
a3
 
< 0.1%
Other values (3)9
 
0.1%
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8435
100.0%

Most frequent character per block

ValueCountFrequency (%)
r2176
25.8%
c1484
17.6%
o1091
12.9%
e1091
12.9%
t1091
12.9%
C692
 
8.2%
I396
 
4.7%
n396
 
4.7%
N3
 
< 0.1%
3
 
< 0.1%
Other values (4)12
 
0.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
687 
Not asked
239 
Correct
165 

Length

Max length9
Median length9
Mean length8.697525206
Min length7

Characters and Unicode

Total characters9489
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowIncorrect
3rd rowNot asked
4th rowNot asked
5th rowIncorrect
ValueCountFrequency (%)
Incorrect687
63.0%
Not asked239
 
21.9%
Correct165
 
15.1%
2021-03-31T16:23:48.190236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:48.265365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect687
51.7%
not239
 
18.0%
asked239
 
18.0%
correct165
 
12.4%

Most occurring characters

ValueCountFrequency (%)
r1704
18.0%
c1539
16.2%
o1091
11.5%
t1091
11.5%
e1091
11.5%
I687
7.2%
n687
7.2%
N239
 
2.5%
239
 
2.5%
a239
 
2.5%
Other values (4)882
9.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8159
86.0%
Uppercase Letter1091
 
11.5%
Space Separator239
 
2.5%

Most frequent character per category

ValueCountFrequency (%)
r1704
20.9%
c1539
18.9%
o1091
13.4%
t1091
13.4%
e1091
13.4%
n687
8.4%
a239
 
2.9%
s239
 
2.9%
k239
 
2.9%
d239
 
2.9%
ValueCountFrequency (%)
I687
63.0%
N239
 
21.9%
C165
 
15.1%
ValueCountFrequency (%)
239
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9250
97.5%
Common239
 
2.5%

Most frequent character per script

ValueCountFrequency (%)
r1704
18.4%
c1539
16.6%
o1091
11.8%
t1091
11.8%
e1091
11.8%
I687
7.4%
n687
7.4%
N239
 
2.6%
a239
 
2.6%
s239
 
2.6%
Other values (3)643
 
7.0%
ValueCountFrequency (%)
239
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9489
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1704
18.0%
c1539
16.2%
o1091
11.5%
t1091
11.5%
e1091
11.5%
I687
7.2%
n687
7.2%
N239
 
2.5%
239
 
2.5%
a239
 
2.5%
Other values (4)882
9.3%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
729 
Correct
352 
Not asked
 
10

Length

Max length9
Median length9
Mean length8.35472044
Min length7

Characters and Unicode

Total characters9115
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCorrect
2nd rowCorrect
3rd rowIncorrect
4th rowIncorrect
5th rowCorrect
ValueCountFrequency (%)
Incorrect729
66.8%
Correct352
32.3%
Not asked10
 
0.9%
2021-03-31T16:23:48.458132image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:48.529754image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect729
66.2%
correct352
32.0%
not10
 
0.9%
asked10
 
0.9%

Most occurring characters

ValueCountFrequency (%)
r2162
23.7%
c1810
19.9%
o1091
12.0%
e1091
12.0%
t1091
12.0%
I729
 
8.0%
n729
 
8.0%
C352
 
3.9%
N10
 
0.1%
10
 
0.1%
Other values (4)40
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8014
87.9%
Uppercase Letter1091
 
12.0%
Space Separator10
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
r2162
27.0%
c1810
22.6%
o1091
13.6%
e1091
13.6%
t1091
13.6%
n729
 
9.1%
a10
 
0.1%
s10
 
0.1%
k10
 
0.1%
d10
 
0.1%
ValueCountFrequency (%)
I729
66.8%
C352
32.3%
N10
 
0.9%
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9105
99.9%
Common10
 
0.1%

Most frequent character per script

ValueCountFrequency (%)
r2162
23.7%
c1810
19.9%
o1091
12.0%
e1091
12.0%
t1091
12.0%
I729
 
8.0%
n729
 
8.0%
C352
 
3.9%
N10
 
0.1%
a10
 
0.1%
Other values (3)30
 
0.3%
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9115
100.0%

Most frequent character per block

ValueCountFrequency (%)
r2162
23.7%
c1810
19.9%
o1091
12.0%
e1091
12.0%
t1091
12.0%
I729
 
8.0%
n729
 
8.0%
C352
 
3.9%
N10
 
0.1%
10
 
0.1%
Other values (4)40
 
0.4%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
604 
Correct
246 
Not asked
241 

Length

Max length9
Median length9
Mean length8.54903758
Min length7

Characters and Unicode

Total characters9327
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Incorrect604
55.4%
Correct246
22.5%
Not asked241
 
22.1%
2021-03-31T16:23:48.751382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:48.823838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect604
45.3%
correct246
18.5%
not241
 
18.1%
asked241
 
18.1%

Most occurring characters

ValueCountFrequency (%)
r1700
18.2%
c1454
15.6%
o1091
11.7%
t1091
11.7%
e1091
11.7%
I604
 
6.5%
n604
 
6.5%
C246
 
2.6%
N241
 
2.6%
241
 
2.6%
Other values (4)964
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7995
85.7%
Uppercase Letter1091
 
11.7%
Space Separator241
 
2.6%

Most frequent character per category

ValueCountFrequency (%)
r1700
21.3%
c1454
18.2%
o1091
13.6%
t1091
13.6%
e1091
13.6%
n604
 
7.6%
a241
 
3.0%
s241
 
3.0%
k241
 
3.0%
d241
 
3.0%
ValueCountFrequency (%)
I604
55.4%
C246
22.5%
N241
 
22.1%
ValueCountFrequency (%)
241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9086
97.4%
Common241
 
2.6%

Most frequent character per script

ValueCountFrequency (%)
r1700
18.7%
c1454
16.0%
o1091
12.0%
t1091
12.0%
e1091
12.0%
I604
 
6.6%
n604
 
6.6%
C246
 
2.7%
N241
 
2.7%
a241
 
2.7%
Other values (3)723
8.0%
ValueCountFrequency (%)
241
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9327
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1700
18.2%
c1454
15.6%
o1091
11.7%
t1091
11.7%
e1091
11.7%
I604
 
6.5%
n604
 
6.5%
C246
 
2.6%
N241
 
2.6%
241
 
2.6%
Other values (4)964
10.3%

OPTIMA DIAGNOSES V 2010: DIAGNOSTIC CODE
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct13
Distinct (%)1.2%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean10.76321101
Minimum0
Maximum9195
Zeros52
Zeros (%)4.8%
Memory size8.6 KiB
2021-03-31T16:23:48.890687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.1
median2
Q34
95-th percentile6
Maximum9195
Range9195
Interquartile range (IQR)3.9

Descriptive statistics

Standard deviation278.4496537
Coefficient of variation (CV)25.87050031
Kurtosis1089.816387
Mean10.76321101
Median Absolute Deviation (MAD)1.9
Skewness33.01098161
Sum11731.9
Variance77534.20966
MonotocityNot monotonic
2021-03-31T16:23:48.974636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.1355
32.5%
4206
18.9%
2125
 
11.5%
3121
 
11.1%
689
 
8.2%
0.267
 
6.1%
052
 
4.8%
1033
 
3.0%
124
 
2.2%
913
 
1.2%
Other values (3)5
 
0.5%
ValueCountFrequency (%)
052
 
4.8%
0.1355
32.5%
0.267
 
6.1%
124
 
2.2%
2125
 
11.5%
ValueCountFrequency (%)
91951
 
0.1%
122
 
0.2%
112
 
0.2%
1033
3.0%
913
 
1.2%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Not asked
712 
No
321 
Yes
 
58

Length

Max length9
Median length9
Mean length6.621448213
Min length2

Characters and Unicode

Total characters7224
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowNot asked
3rd rowNot asked
4th rowNot asked
5th rowNot asked
ValueCountFrequency (%)
Not asked712
65.3%
No321
29.4%
Yes58
 
5.3%
2021-03-31T16:23:49.190158image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:49.262034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
not712
39.5%
asked712
39.5%
no321
17.8%
yes58
 
3.2%

Most occurring characters

ValueCountFrequency (%)
N1033
14.3%
o1033
14.3%
s770
10.7%
e770
10.7%
t712
9.9%
712
9.9%
a712
9.9%
k712
9.9%
d712
9.9%
Y58
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5421
75.0%
Uppercase Letter1091
 
15.1%
Space Separator712
 
9.9%

Most frequent character per category

ValueCountFrequency (%)
o1033
19.1%
s770
14.2%
e770
14.2%
t712
13.1%
a712
13.1%
k712
13.1%
d712
13.1%
ValueCountFrequency (%)
N1033
94.7%
Y58
 
5.3%
ValueCountFrequency (%)
712
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6512
90.1%
Common712
 
9.9%

Most frequent character per script

ValueCountFrequency (%)
N1033
15.9%
o1033
15.9%
s770
11.8%
e770
11.8%
t712
10.9%
a712
10.9%
k712
10.9%
d712
10.9%
Y58
 
0.9%
ValueCountFrequency (%)
712
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII7224
100.0%

Most frequent character per block

ValueCountFrequency (%)
N1033
14.3%
o1033
14.3%
s770
10.7%
e770
10.7%
t712
9.9%
712
9.9%
a712
9.9%
k712
9.9%
d712
9.9%
Y58
 
0.8%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Not asked
597 
Negative
480 
Possible
 
11
Probable
 
3

Length

Max length9
Median length9
Mean length8.5472044
Min length8

Characters and Unicode

Total characters9325
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNegative
2nd rowNegative
3rd rowNegative
4th rowNegative
5th rowNegative
ValueCountFrequency (%)
Not asked597
54.7%
Negative480
44.0%
Possible11
 
1.0%
Probable3
 
0.3%
2021-03-31T16:23:49.447330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:49.532078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
not597
35.4%
asked597
35.4%
negative480
28.4%
possible11
 
0.7%
probable3
 
0.2%

Most occurring characters

ValueCountFrequency (%)
e1571
16.8%
a1080
11.6%
N1077
11.5%
t1077
11.5%
s619
 
6.6%
o611
 
6.6%
597
 
6.4%
k597
 
6.4%
d597
 
6.4%
i491
 
5.3%
Other values (6)1008
10.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7637
81.9%
Uppercase Letter1091
 
11.7%
Space Separator597
 
6.4%

Most frequent character per category

ValueCountFrequency (%)
e1571
20.6%
a1080
14.1%
t1077
14.1%
s619
 
8.1%
o611
 
8.0%
k597
 
7.8%
d597
 
7.8%
i491
 
6.4%
g480
 
6.3%
v480
 
6.3%
Other values (3)34
 
0.4%
ValueCountFrequency (%)
N1077
98.7%
P14
 
1.3%
ValueCountFrequency (%)
597
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8728
93.6%
Common597
 
6.4%

Most frequent character per script

ValueCountFrequency (%)
e1571
18.0%
a1080
12.4%
N1077
12.3%
t1077
12.3%
s619
 
7.1%
o611
 
7.0%
k597
 
6.8%
d597
 
6.8%
i491
 
5.6%
g480
 
5.5%
Other values (5)528
 
6.0%
ValueCountFrequency (%)
597
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9325
100.0%

Most frequent character per block

ValueCountFrequency (%)
e1571
16.8%
a1080
11.6%
N1077
11.5%
t1077
11.5%
s619
 
6.6%
o611
 
6.6%
597
 
6.4%
k597
 
6.4%
d597
 
6.4%
i491
 
5.3%
Other values (6)1008
10.8%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
574 
Correct
279 
Not asked
238 

Length

Max length9
Median length9
Mean length8.488542621
Min length7

Characters and Unicode

Total characters9261
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Incorrect574
52.6%
Correct279
25.6%
Not asked238
21.8%
2021-03-31T16:23:49.761650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:49.843334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect574
43.2%
correct279
21.0%
not238
17.9%
asked238
17.9%

Most occurring characters

ValueCountFrequency (%)
r1706
18.4%
c1427
15.4%
o1091
11.8%
t1091
11.8%
e1091
11.8%
I574
 
6.2%
n574
 
6.2%
C279
 
3.0%
N238
 
2.6%
238
 
2.6%
Other values (4)952
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7932
85.6%
Uppercase Letter1091
 
11.8%
Space Separator238
 
2.6%

Most frequent character per category

ValueCountFrequency (%)
r1706
21.5%
c1427
18.0%
o1091
13.8%
t1091
13.8%
e1091
13.8%
n574
 
7.2%
a238
 
3.0%
s238
 
3.0%
k238
 
3.0%
d238
 
3.0%
ValueCountFrequency (%)
I574
52.6%
C279
25.6%
N238
21.8%
ValueCountFrequency (%)
238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9023
97.4%
Common238
 
2.6%

Most frequent character per script

ValueCountFrequency (%)
r1706
18.9%
c1427
15.8%
o1091
12.1%
t1091
12.1%
e1091
12.1%
I574
 
6.4%
n574
 
6.4%
C279
 
3.1%
N238
 
2.6%
a238
 
2.6%
Other values (3)714
7.9%
ValueCountFrequency (%)
238
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9261
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1706
18.4%
c1427
15.4%
o1091
11.8%
t1091
11.8%
e1091
11.8%
I574
 
6.2%
n574
 
6.2%
C279
 
3.0%
N238
 
2.6%
238
 
2.6%
Other values (4)952
10.3%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
664 
Not asked
243 
One error
105 
> two errors
79 

Length

Max length12
Median length7
Mean length8
Min length7

Characters and Unicode

Total characters8728
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct664
60.9%
Not asked243
 
22.3%
One error105
 
9.6%
> two errors79
 
7.2%
2021-03-31T16:23:50.043988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:50.107394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct664
41.6%
not243
 
15.2%
asked243
 
15.2%
one105
 
6.6%
error105
 
6.6%
errors79
 
4.9%
two79
 
4.9%
79
 
4.9%

Most occurring characters

ValueCountFrequency (%)
r1880
21.5%
e1196
13.7%
o1170
13.4%
t986
11.3%
C664
 
7.6%
c664
 
7.6%
506
 
5.8%
s322
 
3.7%
N243
 
2.8%
a243
 
2.8%
Other values (6)854
9.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7131
81.7%
Uppercase Letter1012
 
11.6%
Space Separator506
 
5.8%
Math Symbol79
 
0.9%

Most frequent character per category

ValueCountFrequency (%)
r1880
26.4%
e1196
16.8%
o1170
16.4%
t986
13.8%
c664
 
9.3%
s322
 
4.5%
a243
 
3.4%
k243
 
3.4%
d243
 
3.4%
n105
 
1.5%
ValueCountFrequency (%)
C664
65.6%
N243
 
24.0%
O105
 
10.4%
ValueCountFrequency (%)
506
100.0%
ValueCountFrequency (%)
>79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8143
93.3%
Common585
 
6.7%

Most frequent character per script

ValueCountFrequency (%)
r1880
23.1%
e1196
14.7%
o1170
14.4%
t986
12.1%
C664
 
8.2%
c664
 
8.2%
s322
 
4.0%
N243
 
3.0%
a243
 
3.0%
k243
 
3.0%
Other values (4)532
 
6.5%
ValueCountFrequency (%)
506
86.5%
>79
 
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII8728
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1880
21.5%
e1196
13.7%
o1170
13.4%
t986
11.3%
C664
 
7.6%
c664
 
7.6%
506
 
5.8%
s322
 
3.7%
N243
 
2.8%
a243
 
2.8%
Other values (6)854
9.8%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
625 
Correct
465 
Not asked
 
1

Length

Max length9
Median length9
Mean length8.147571036
Min length7

Characters and Unicode

Total characters8889
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowCorrect
2nd rowCorrect
3rd rowCorrect
4th rowCorrect
5th rowIncorrect
ValueCountFrequency (%)
Incorrect625
57.3%
Correct465
42.6%
Not asked1
 
0.1%
2021-03-31T16:23:50.301059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:50.380896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect625
57.2%
correct465
42.6%
not1
 
0.1%
asked1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
r2180
24.5%
c1715
19.3%
o1091
12.3%
e1091
12.3%
t1091
12.3%
I625
 
7.0%
n625
 
7.0%
C465
 
5.2%
N1
 
< 0.1%
1
 
< 0.1%
Other values (4)4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7797
87.7%
Uppercase Letter1091
 
12.3%
Space Separator1
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
r2180
28.0%
c1715
22.0%
o1091
14.0%
e1091
14.0%
t1091
14.0%
n625
 
8.0%
a1
 
< 0.1%
s1
 
< 0.1%
k1
 
< 0.1%
d1
 
< 0.1%
ValueCountFrequency (%)
I625
57.3%
C465
42.6%
N1
 
0.1%
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8888
> 99.9%
Common1
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
r2180
24.5%
c1715
19.3%
o1091
12.3%
e1091
12.3%
t1091
12.3%
I625
 
7.0%
n625
 
7.0%
C465
 
5.2%
N1
 
< 0.1%
a1
 
< 0.1%
Other values (3)3
 
< 0.1%
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8889
100.0%

Most frequent character per block

ValueCountFrequency (%)
r2180
24.5%
c1715
19.3%
o1091
12.3%
e1091
12.3%
t1091
12.3%
I625
 
7.0%
n625
 
7.0%
C465
 
5.2%
N1
 
< 0.1%
1
 
< 0.1%
Other values (4)4
 
< 0.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
613 
Correct
468 
Not asked
 
10

Length

Max length9
Median length9
Mean length8.142071494
Min length7

Characters and Unicode

Total characters8883
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCorrect
2nd rowIncorrect
3rd rowIncorrect
4th rowCorrect
5th rowIncorrect
ValueCountFrequency (%)
Incorrect613
56.2%
Correct468
42.9%
Not asked10
 
0.9%
2021-03-31T16:23:50.594373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:50.666058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect613
55.7%
correct468
42.5%
not10
 
0.9%
asked10
 
0.9%

Most occurring characters

ValueCountFrequency (%)
r2162
24.3%
c1694
19.1%
o1091
12.3%
e1091
12.3%
t1091
12.3%
I613
 
6.9%
n613
 
6.9%
C468
 
5.3%
N10
 
0.1%
10
 
0.1%
Other values (4)40
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7782
87.6%
Uppercase Letter1091
 
12.3%
Space Separator10
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
r2162
27.8%
c1694
21.8%
o1091
14.0%
e1091
14.0%
t1091
14.0%
n613
 
7.9%
a10
 
0.1%
s10
 
0.1%
k10
 
0.1%
d10
 
0.1%
ValueCountFrequency (%)
I613
56.2%
C468
42.9%
N10
 
0.9%
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8873
99.9%
Common10
 
0.1%

Most frequent character per script

ValueCountFrequency (%)
r2162
24.4%
c1694
19.1%
o1091
12.3%
e1091
12.3%
t1091
12.3%
I613
 
6.9%
n613
 
6.9%
C468
 
5.3%
N10
 
0.1%
a10
 
0.1%
Other values (3)30
 
0.3%
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8883
100.0%

Most frequent character per block

ValueCountFrequency (%)
r2162
24.3%
c1694
19.1%
o1091
12.3%
e1091
12.3%
t1091
12.3%
I613
 
6.9%
n613
 
6.9%
C468
 
5.3%
N10
 
0.1%
10
 
0.1%
Other values (4)40
 
0.5%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
448 
Correct
402 
Not asked
241 

Length

Max length9
Median length9
Mean length8.263061412
Min length7

Characters and Unicode

Total characters9015
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Incorrect448
41.1%
Correct402
36.8%
Not asked241
22.1%
2021-03-31T16:23:50.855790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:50.934604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect448
33.6%
correct402
30.2%
not241
18.1%
asked241
18.1%

Most occurring characters

ValueCountFrequency (%)
r1700
18.9%
c1298
14.4%
o1091
12.1%
t1091
12.1%
e1091
12.1%
I448
 
5.0%
n448
 
5.0%
C402
 
4.5%
N241
 
2.7%
241
 
2.7%
Other values (4)964
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7683
85.2%
Uppercase Letter1091
 
12.1%
Space Separator241
 
2.7%

Most frequent character per category

ValueCountFrequency (%)
r1700
22.1%
c1298
16.9%
o1091
14.2%
t1091
14.2%
e1091
14.2%
n448
 
5.8%
a241
 
3.1%
s241
 
3.1%
k241
 
3.1%
d241
 
3.1%
ValueCountFrequency (%)
I448
41.1%
C402
36.8%
N241
22.1%
ValueCountFrequency (%)
241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8774
97.3%
Common241
 
2.7%

Most frequent character per script

ValueCountFrequency (%)
r1700
19.4%
c1298
14.8%
o1091
12.4%
t1091
12.4%
e1091
12.4%
I448
 
5.1%
n448
 
5.1%
C402
 
4.6%
N241
 
2.7%
a241
 
2.7%
Other values (3)723
8.2%
ValueCountFrequency (%)
241
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9015
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1700
18.9%
c1298
14.4%
o1091
12.1%
t1091
12.1%
e1091
12.1%
I448
 
5.0%
n448
 
5.0%
C402
 
4.5%
N241
 
2.7%
241
 
2.7%
Other values (4)964
10.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
580 
Correct
273 
Not asked
238 

Length

Max length9
Median length9
Mean length8.499541705
Min length7

Characters and Unicode

Total characters9273
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowIncorrect
3rd rowNot asked
4th rowNot asked
5th rowIncorrect
ValueCountFrequency (%)
Incorrect580
53.2%
Correct273
25.0%
Not asked238
21.8%
2021-03-31T16:23:51.139986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:51.221445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect580
43.6%
correct273
20.5%
not238
17.9%
asked238
17.9%

Most occurring characters

ValueCountFrequency (%)
r1706
18.4%
c1433
15.5%
o1091
11.8%
t1091
11.8%
e1091
11.8%
I580
 
6.3%
n580
 
6.3%
C273
 
2.9%
N238
 
2.6%
238
 
2.6%
Other values (4)952
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7944
85.7%
Uppercase Letter1091
 
11.8%
Space Separator238
 
2.6%

Most frequent character per category

ValueCountFrequency (%)
r1706
21.5%
c1433
18.0%
o1091
13.7%
t1091
13.7%
e1091
13.7%
n580
 
7.3%
a238
 
3.0%
s238
 
3.0%
k238
 
3.0%
d238
 
3.0%
ValueCountFrequency (%)
I580
53.2%
C273
25.0%
N238
21.8%
ValueCountFrequency (%)
238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9035
97.4%
Common238
 
2.6%

Most frequent character per script

ValueCountFrequency (%)
r1706
18.9%
c1433
15.9%
o1091
12.1%
t1091
12.1%
e1091
12.1%
I580
 
6.4%
n580
 
6.4%
C273
 
3.0%
N238
 
2.6%
a238
 
2.6%
Other values (3)714
7.9%
ValueCountFrequency (%)
238
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9273
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1706
18.4%
c1433
15.5%
o1091
11.8%
t1091
11.8%
e1091
11.8%
I580
 
6.3%
n580
 
6.3%
C273
 
2.9%
N238
 
2.6%
238
 
2.6%
Other values (4)952
10.3%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
635 
Not asked
237 
Incorrect
219 

Length

Max length9
Median length7
Mean length7.835930339
Min length7

Characters and Unicode

Total characters8549
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct635
58.2%
Not asked237
 
21.7%
Incorrect219
 
20.1%
2021-03-31T16:23:51.415543image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:51.493009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct635
47.8%
not237
 
17.8%
asked237
 
17.8%
incorrect219
 
16.5%

Most occurring characters

ValueCountFrequency (%)
r1708
20.0%
o1091
12.8%
t1091
12.8%
e1091
12.8%
c1073
12.6%
C635
 
7.4%
N237
 
2.8%
237
 
2.8%
a237
 
2.8%
s237
 
2.8%
Other values (4)912
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7221
84.5%
Uppercase Letter1091
 
12.8%
Space Separator237
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1708
23.7%
o1091
15.1%
t1091
15.1%
e1091
15.1%
c1073
14.9%
a237
 
3.3%
s237
 
3.3%
k237
 
3.3%
d237
 
3.3%
n219
 
3.0%
ValueCountFrequency (%)
C635
58.2%
N237
 
21.7%
I219
 
20.1%
ValueCountFrequency (%)
237
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8312
97.2%
Common237
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1708
20.5%
o1091
13.1%
t1091
13.1%
e1091
13.1%
c1073
12.9%
C635
 
7.6%
N237
 
2.9%
a237
 
2.9%
s237
 
2.9%
k237
 
2.9%
Other values (3)675
 
8.1%
ValueCountFrequency (%)
237
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8549
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1708
20.0%
o1091
12.8%
t1091
12.8%
e1091
12.8%
c1073
12.6%
C635
 
7.4%
N237
 
2.8%
237
 
2.8%
a237
 
2.8%
s237
 
2.8%
Other values (4)912
10.7%
Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Negative
813 
Not asked
122 
Possible
118 
Probable
 
34
Not known
 
4

Length

Max length9
Median length8
Mean length8.115490376
Min length8

Characters and Unicode

Total characters8854
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNegative
2nd rowNegative
3rd rowNegative
4th rowNegative
5th rowNegative
ValueCountFrequency (%)
Negative813
74.5%
Not asked122
 
11.2%
Possible118
 
10.8%
Probable34
 
3.1%
Not known4
 
0.4%
2021-03-31T16:23:51.711801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:51.781222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
negative813
66.8%
not126
 
10.4%
asked122
 
10.0%
possible118
 
9.7%
probable34
 
2.8%
known4
 
0.3%

Most occurring characters

ValueCountFrequency (%)
e1900
21.5%
a969
10.9%
N939
10.6%
t939
10.6%
i931
10.5%
g813
9.2%
v813
9.2%
s358
 
4.0%
o282
 
3.2%
b186
 
2.1%
Other values (8)724
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7637
86.3%
Uppercase Letter1091
 
12.3%
Space Separator126
 
1.4%

Most frequent character per category

ValueCountFrequency (%)
e1900
24.9%
a969
12.7%
t939
12.3%
i931
12.2%
g813
10.6%
v813
10.6%
s358
 
4.7%
o282
 
3.7%
b186
 
2.4%
l152
 
2.0%
Other values (5)294
 
3.8%
ValueCountFrequency (%)
N939
86.1%
P152
 
13.9%
ValueCountFrequency (%)
126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8728
98.6%
Common126
 
1.4%

Most frequent character per script

ValueCountFrequency (%)
e1900
21.8%
a969
11.1%
N939
10.8%
t939
10.8%
i931
10.7%
g813
9.3%
v813
9.3%
s358
 
4.1%
o282
 
3.2%
b186
 
2.1%
Other values (7)598
 
6.9%
ValueCountFrequency (%)
126
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8854
100.0%

Most frequent character per block

ValueCountFrequency (%)
e1900
21.5%
a969
10.9%
N939
10.6%
t939
10.6%
i931
10.5%
g813
9.2%
v813
9.2%
s358
 
4.0%
o282
 
3.2%
b186
 
2.1%
Other values (8)724
 
8.2%
Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
No
576 
Mild
354 
Not asked
123 
Moderate
 
35
Severe
 
2

Length

Max length9
Median length2
Mean length3.64436297
Min length2

Characters and Unicode

Total characters3976
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
No576
52.8%
Mild354
32.4%
Not asked123
 
11.3%
Moderate35
 
3.2%
Severe2
 
0.2%
Not known1
 
0.1%
2021-03-31T16:23:51.994305image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:52.074636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
no576
47.4%
mild354
29.1%
not124
 
10.2%
asked123
 
10.1%
moderate35
 
2.9%
severe2
 
0.2%
known1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
o736
18.5%
N700
17.6%
d512
12.9%
M389
9.8%
i354
8.9%
l354
8.9%
e199
 
5.0%
t159
 
4.0%
a158
 
4.0%
124
 
3.1%
Other values (7)291
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2761
69.4%
Uppercase Letter1091
 
27.4%
Space Separator124
 
3.1%

Most frequent character per category

ValueCountFrequency (%)
o736
26.7%
d512
18.5%
i354
12.8%
l354
12.8%
e199
 
7.2%
t159
 
5.8%
a158
 
5.7%
k124
 
4.5%
s123
 
4.5%
r37
 
1.3%
Other values (3)5
 
0.2%
ValueCountFrequency (%)
N700
64.2%
M389
35.7%
S2
 
0.2%
ValueCountFrequency (%)
124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3852
96.9%
Common124
 
3.1%

Most frequent character per script

ValueCountFrequency (%)
o736
19.1%
N700
18.2%
d512
13.3%
M389
10.1%
i354
9.2%
l354
9.2%
e199
 
5.2%
t159
 
4.1%
a158
 
4.1%
k124
 
3.2%
Other values (6)167
 
4.3%
ValueCountFrequency (%)
124
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3976
100.0%

Most frequent character per block

ValueCountFrequency (%)
o736
18.5%
N700
17.6%
d512
12.9%
M389
9.8%
i354
8.9%
l354
8.9%
e199
 
5.0%
t159
 
4.0%
a158
 
4.0%
124
 
3.1%
Other values (7)291
 
7.3%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Yes
863 
Not asked
116 
No
110 
Not known
 
2

Length

Max length9
Median length3
Mean length3.54812099
Min length2

Characters and Unicode

Total characters3871
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
Yes863
79.1%
Not asked116
 
10.6%
No110
 
10.1%
Not known2
 
0.2%
2021-03-31T16:23:52.279784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:52.354066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
yes863
71.4%
not118
 
9.8%
asked116
 
9.6%
no110
 
9.1%
known2
 
0.2%

Most occurring characters

ValueCountFrequency (%)
e979
25.3%
s979
25.3%
Y863
22.3%
o230
 
5.9%
N228
 
5.9%
t118
 
3.0%
118
 
3.0%
k118
 
3.0%
a116
 
3.0%
d116
 
3.0%
Other values (2)6
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2662
68.8%
Uppercase Letter1091
28.2%
Space Separator118
 
3.0%

Most frequent character per category

ValueCountFrequency (%)
e979
36.8%
s979
36.8%
o230
 
8.6%
t118
 
4.4%
k118
 
4.4%
a116
 
4.4%
d116
 
4.4%
n4
 
0.2%
w2
 
0.1%
ValueCountFrequency (%)
Y863
79.1%
N228
 
20.9%
ValueCountFrequency (%)
118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3753
97.0%
Common118
 
3.0%

Most frequent character per script

ValueCountFrequency (%)
e979
26.1%
s979
26.1%
Y863
23.0%
o230
 
6.1%
N228
 
6.1%
t118
 
3.1%
k118
 
3.1%
a116
 
3.1%
d116
 
3.1%
n4
 
0.1%
ValueCountFrequency (%)
118
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3871
100.0%

Most frequent character per block

ValueCountFrequency (%)
e979
25.3%
s979
25.3%
Y863
22.3%
o230
 
5.9%
N228
 
5.9%
t118
 
3.0%
118
 
3.0%
k118
 
3.0%
a116
 
3.0%
d116
 
3.0%
Other values (2)6
 
0.2%
Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
None
498 
Mild
158 
No scan
134 
Moderate
130 
Not asked
83 
Other values (2)
88 

Length

Max length9
Median length4
Mean length5.58203483
Min length4

Characters and Unicode

Total characters6090
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot known
2nd rowNone
3rd rowNot known
4th rowNot known
5th rowNone
ValueCountFrequency (%)
None498
45.6%
Mild158
 
14.5%
No scan134
 
12.3%
Moderate130
 
11.9%
Not asked83
 
7.6%
Not known71
 
6.5%
Severe17
 
1.6%
2021-03-31T16:23:52.760578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:52.828602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
none498
36.1%
mild158
 
11.5%
not154
 
11.2%
scan134
 
9.7%
no134
 
9.7%
moderate130
 
9.4%
asked83
 
6.0%
known71
 
5.1%
severe17
 
1.2%

Most occurring characters

ValueCountFrequency (%)
o987
16.2%
e892
14.6%
N786
12.9%
n774
12.7%
d371
 
6.1%
a347
 
5.7%
288
 
4.7%
M288
 
4.7%
t284
 
4.7%
s217
 
3.6%
Other values (8)856
14.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4711
77.4%
Uppercase Letter1091
 
17.9%
Space Separator288
 
4.7%

Most frequent character per category

ValueCountFrequency (%)
o987
21.0%
e892
18.9%
n774
16.4%
d371
 
7.9%
a347
 
7.4%
t284
 
6.0%
s217
 
4.6%
i158
 
3.4%
l158
 
3.4%
k154
 
3.3%
Other values (4)369
 
7.8%
ValueCountFrequency (%)
N786
72.0%
M288
 
26.4%
S17
 
1.6%
ValueCountFrequency (%)
288
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5802
95.3%
Common288
 
4.7%

Most frequent character per script

ValueCountFrequency (%)
o987
17.0%
e892
15.4%
N786
13.5%
n774
13.3%
d371
 
6.4%
a347
 
6.0%
M288
 
5.0%
t284
 
4.9%
s217
 
3.7%
i158
 
2.7%
Other values (7)698
12.0%
ValueCountFrequency (%)
288
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6090
100.0%

Most frequent character per block

ValueCountFrequency (%)
o987
16.2%
e892
14.6%
N786
12.9%
n774
12.7%
d371
 
6.1%
a347
 
5.7%
288
 
4.7%
M288
 
4.7%
t284
 
4.7%
s217
 
3.6%
Other values (8)856
14.1%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
No
734 
Yes
220 
Not asked
130 
Not known
 
7

Length

Max length9
Median length2
Mean length3.080659945
Min length2

Characters and Unicode

Total characters3361
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
No734
67.3%
Yes220
 
20.2%
Not asked130
 
11.9%
Not known7
 
0.6%
2021-03-31T16:23:53.105040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:53.178270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
no734
59.8%
yes220
 
17.9%
not137
 
11.2%
asked130
 
10.6%
known7
 
0.6%

Most occurring characters

ValueCountFrequency (%)
o878
26.1%
N871
25.9%
e350
 
10.4%
s350
 
10.4%
Y220
 
6.5%
t137
 
4.1%
137
 
4.1%
k137
 
4.1%
a130
 
3.9%
d130
 
3.9%
Other values (2)21
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2133
63.5%
Uppercase Letter1091
32.5%
Space Separator137
 
4.1%

Most frequent character per category

ValueCountFrequency (%)
o878
41.2%
e350
 
16.4%
s350
 
16.4%
t137
 
6.4%
k137
 
6.4%
a130
 
6.1%
d130
 
6.1%
n14
 
0.7%
w7
 
0.3%
ValueCountFrequency (%)
N871
79.8%
Y220
 
20.2%
ValueCountFrequency (%)
137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3224
95.9%
Common137
 
4.1%

Most frequent character per script

ValueCountFrequency (%)
o878
27.2%
N871
27.0%
e350
 
10.9%
s350
 
10.9%
Y220
 
6.8%
t137
 
4.2%
k137
 
4.2%
a130
 
4.0%
d130
 
4.0%
n14
 
0.4%
ValueCountFrequency (%)
137
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3361
100.0%

Most frequent character per block

ValueCountFrequency (%)
o878
26.1%
N871
25.9%
e350
 
10.4%
s350
 
10.4%
Y220
 
6.5%
t137
 
4.1%
137
 
4.1%
k137
 
4.1%
a130
 
3.9%
d130
 
3.9%
Other values (2)21
 
0.6%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
521 
Incorrect
328 
Not asked
242 

Length

Max length9
Median length9
Mean length8.044912924
Min length7

Characters and Unicode

Total characters8777
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct521
47.8%
Incorrect328
30.1%
Not asked242
22.2%
2021-03-31T16:23:53.378759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:53.455796image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct521
39.1%
incorrect328
24.6%
not242
18.2%
asked242
18.2%

Most occurring characters

ValueCountFrequency (%)
r1698
19.3%
c1177
13.4%
o1091
12.4%
t1091
12.4%
e1091
12.4%
C521
 
5.9%
I328
 
3.7%
n328
 
3.7%
N242
 
2.8%
242
 
2.8%
Other values (4)968
11.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7444
84.8%
Uppercase Letter1091
 
12.4%
Space Separator242
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1698
22.8%
c1177
15.8%
o1091
14.7%
t1091
14.7%
e1091
14.7%
n328
 
4.4%
a242
 
3.3%
s242
 
3.3%
k242
 
3.3%
d242
 
3.3%
ValueCountFrequency (%)
C521
47.8%
I328
30.1%
N242
22.2%
ValueCountFrequency (%)
242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8535
97.2%
Common242
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1698
19.9%
c1177
13.8%
o1091
12.8%
t1091
12.8%
e1091
12.8%
C521
 
6.1%
I328
 
3.8%
n328
 
3.8%
N242
 
2.8%
a242
 
2.8%
Other values (3)726
8.5%
ValueCountFrequency (%)
242
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8777
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1698
19.3%
c1177
13.4%
o1091
12.4%
t1091
12.4%
e1091
12.4%
C521
 
5.9%
I328
 
3.7%
n328
 
3.7%
N242
 
2.8%
242
 
2.8%
Other values (4)968
11.0%
Distinct3
Distinct (%)0.3%
Missing1
Missing (%)0.1%
Memory size8.6 KiB
Correct
707 
Not asked
242 
Incorrect
141 

Length

Max length9
Median length7
Mean length7.702752294
Min length7

Characters and Unicode

Total characters8396
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct707
64.8%
Not asked242
 
22.2%
Incorrect141
 
12.9%
(Missing)1
 
0.1%
2021-03-31T16:23:53.649062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:53.724190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct707
53.1%
not242
 
18.2%
asked242
 
18.2%
incorrect141
 
10.6%

Most occurring characters

ValueCountFrequency (%)
r1696
20.2%
o1090
13.0%
t1090
13.0%
e1090
13.0%
c989
11.8%
C707
8.4%
N242
 
2.9%
242
 
2.9%
a242
 
2.9%
s242
 
2.9%
Other values (4)766
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7064
84.1%
Uppercase Letter1090
 
13.0%
Space Separator242
 
2.9%

Most frequent character per category

ValueCountFrequency (%)
r1696
24.0%
o1090
15.4%
t1090
15.4%
e1090
15.4%
c989
14.0%
a242
 
3.4%
s242
 
3.4%
k242
 
3.4%
d242
 
3.4%
n141
 
2.0%
ValueCountFrequency (%)
C707
64.9%
N242
 
22.2%
I141
 
12.9%
ValueCountFrequency (%)
242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8154
97.1%
Common242
 
2.9%

Most frequent character per script

ValueCountFrequency (%)
r1696
20.8%
o1090
13.4%
t1090
13.4%
e1090
13.4%
c989
12.1%
C707
8.7%
N242
 
3.0%
a242
 
3.0%
s242
 
3.0%
k242
 
3.0%
Other values (3)524
 
6.4%
ValueCountFrequency (%)
242
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8396
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1696
20.2%
o1090
13.0%
t1090
13.0%
e1090
13.0%
c989
11.8%
C707
8.4%
N242
 
2.9%
242
 
2.9%
a242
 
2.9%
s242
 
2.9%
Other values (4)766
9.1%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Incorrect
746 
Not asked
238 
Correct
107 

Length

Max length9
Median length9
Mean length8.803849679
Min length7

Characters and Unicode

Total characters9605
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowIncorrect
3rd rowNot asked
4th rowNot asked
5th rowIncorrect
ValueCountFrequency (%)
Incorrect746
68.4%
Not asked238
 
21.8%
Correct107
 
9.8%
2021-03-31T16:23:53.918992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:54.008991image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
incorrect746
56.1%
not238
 
17.9%
asked238
 
17.9%
correct107
 
8.1%

Most occurring characters

ValueCountFrequency (%)
r1706
17.8%
c1599
16.6%
o1091
11.4%
t1091
11.4%
e1091
11.4%
I746
7.8%
n746
7.8%
N238
 
2.5%
238
 
2.5%
a238
 
2.5%
Other values (4)821
8.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8276
86.2%
Uppercase Letter1091
 
11.4%
Space Separator238
 
2.5%

Most frequent character per category

ValueCountFrequency (%)
r1706
20.6%
c1599
19.3%
o1091
13.2%
t1091
13.2%
e1091
13.2%
n746
9.0%
a238
 
2.9%
s238
 
2.9%
k238
 
2.9%
d238
 
2.9%
ValueCountFrequency (%)
I746
68.4%
N238
 
21.8%
C107
 
9.8%
ValueCountFrequency (%)
238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9367
97.5%
Common238
 
2.5%

Most frequent character per script

ValueCountFrequency (%)
r1706
18.2%
c1599
17.1%
o1091
11.6%
t1091
11.6%
e1091
11.6%
I746
8.0%
n746
8.0%
N238
 
2.5%
a238
 
2.5%
s238
 
2.5%
Other values (3)583
 
6.2%
ValueCountFrequency (%)
238
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9605
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1706
17.8%
c1599
16.6%
o1091
11.4%
t1091
11.4%
e1091
11.4%
I746
7.8%
n746
7.8%
N238
 
2.5%
238
 
2.5%
a238
 
2.5%
Other values (4)821
8.5%

COGNITIVE EXAM 120-161: (160) SUBTRACTING SEVENS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)0.7%
Missing17
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean3.795158287
Minimum0
Maximum9
Zeros85
Zeros (%)7.8%
Memory size8.6 KiB
2021-03-31T16:23:54.079775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median5
Q35
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.702729245
Coefficient of variation (CV)0.4486582946
Kurtosis-0.01735014839
Mean3.795158287
Median Absolute Deviation (MAD)0
Skewness-1.096800598
Sum4076
Variance2.899286881
MonotocityNot monotonic
2021-03-31T16:23:54.204956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5585
53.6%
4173
 
15.9%
197
 
8.9%
085
 
7.8%
380
 
7.3%
252
 
4.8%
92
 
0.2%
(Missing)17
 
1.6%
ValueCountFrequency (%)
085
7.8%
197
8.9%
252
 
4.8%
380
7.3%
4173
15.9%
ValueCountFrequency (%)
92
 
0.2%
5585
53.6%
4173
 
15.9%
380
 
7.3%
252
 
4.8%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Not asked
535 
No
462 
Yes
94 

Length

Max length9
Median length3
Mean length5.518790101
Min length2

Characters and Unicode

Total characters6021
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowNot asked
3rd rowNot asked
4th rowNot asked
5th rowNot asked
ValueCountFrequency (%)
Not asked535
49.0%
No462
42.3%
Yes94
 
8.6%
2021-03-31T16:23:54.439668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:54.509218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
not535
32.9%
asked535
32.9%
no462
28.4%
yes94
 
5.8%

Most occurring characters

ValueCountFrequency (%)
N997
16.6%
o997
16.6%
s629
10.4%
e629
10.4%
t535
8.9%
535
8.9%
a535
8.9%
k535
8.9%
d535
8.9%
Y94
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4395
73.0%
Uppercase Letter1091
 
18.1%
Space Separator535
 
8.9%

Most frequent character per category

ValueCountFrequency (%)
o997
22.7%
s629
14.3%
e629
14.3%
t535
12.2%
a535
12.2%
k535
12.2%
d535
12.2%
ValueCountFrequency (%)
N997
91.4%
Y94
 
8.6%
ValueCountFrequency (%)
535
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5486
91.1%
Common535
 
8.9%

Most frequent character per script

ValueCountFrequency (%)
N997
18.2%
o997
18.2%
s629
11.5%
e629
11.5%
t535
9.8%
a535
9.8%
k535
9.8%
d535
9.8%
Y94
 
1.7%
ValueCountFrequency (%)
535
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6021
100.0%

Most frequent character per block

ValueCountFrequency (%)
N997
16.6%
o997
16.6%
s629
10.4%
e629
10.4%
t535
8.9%
535
8.9%
a535
8.9%
k535
8.9%
d535
8.9%
Y94
 
1.6%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
554 
Incorrect
297 
Not asked
240 

Length

Max length9
Median length7
Mean length7.984417965
Min length7

Characters and Unicode

Total characters8711
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct554
50.8%
Incorrect297
27.2%
Not asked240
22.0%
2021-03-31T16:23:54.717613image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:54.833458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct554
41.6%
incorrect297
22.3%
not240
18.0%
asked240
18.0%

Most occurring characters

ValueCountFrequency (%)
r1702
19.5%
c1148
13.2%
o1091
12.5%
t1091
12.5%
e1091
12.5%
C554
 
6.4%
I297
 
3.4%
n297
 
3.4%
N240
 
2.8%
240
 
2.8%
Other values (4)960
11.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7380
84.7%
Uppercase Letter1091
 
12.5%
Space Separator240
 
2.8%

Most frequent character per category

ValueCountFrequency (%)
r1702
23.1%
c1148
15.6%
o1091
14.8%
t1091
14.8%
e1091
14.8%
n297
 
4.0%
a240
 
3.3%
s240
 
3.3%
k240
 
3.3%
d240
 
3.3%
ValueCountFrequency (%)
C554
50.8%
I297
27.2%
N240
22.0%
ValueCountFrequency (%)
240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8471
97.2%
Common240
 
2.8%

Most frequent character per script

ValueCountFrequency (%)
r1702
20.1%
c1148
13.6%
o1091
12.9%
t1091
12.9%
e1091
12.9%
C554
 
6.5%
I297
 
3.5%
n297
 
3.5%
N240
 
2.8%
a240
 
2.8%
Other values (3)720
8.5%
ValueCountFrequency (%)
240
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8711
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1702
19.5%
c1148
13.2%
o1091
12.5%
t1091
12.5%
e1091
12.5%
C554
 
6.4%
I297
 
3.4%
n297
 
3.4%
N240
 
2.8%
240
 
2.8%
Other values (4)960
11.0%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
No
945 
Not asked
127 
Yes
 
19

Length

Max length9
Median length2
Mean length2.832263978
Min length2

Characters and Unicode

Total characters3090
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
No945
86.6%
Not asked127
 
11.6%
Yes19
 
1.7%
2021-03-31T16:23:55.009527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:55.079396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
no945
77.6%
not127
 
10.4%
asked127
 
10.4%
yes19
 
1.6%

Most occurring characters

ValueCountFrequency (%)
N1072
34.7%
o1072
34.7%
s146
 
4.7%
e146
 
4.7%
t127
 
4.1%
127
 
4.1%
a127
 
4.1%
k127
 
4.1%
d127
 
4.1%
Y19
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1872
60.6%
Uppercase Letter1091
35.3%
Space Separator127
 
4.1%

Most frequent character per category

ValueCountFrequency (%)
o1072
57.3%
s146
 
7.8%
e146
 
7.8%
t127
 
6.8%
a127
 
6.8%
k127
 
6.8%
d127
 
6.8%
ValueCountFrequency (%)
N1072
98.3%
Y19
 
1.7%
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2963
95.9%
Common127
 
4.1%

Most frequent character per script

ValueCountFrequency (%)
N1072
36.2%
o1072
36.2%
s146
 
4.9%
e146
 
4.9%
t127
 
4.3%
a127
 
4.3%
k127
 
4.3%
d127
 
4.3%
Y19
 
0.6%
ValueCountFrequency (%)
127
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3090
100.0%

Most frequent character per block

ValueCountFrequency (%)
N1072
34.7%
o1072
34.7%
s146
 
4.7%
e146
 
4.7%
t127
 
4.1%
127
 
4.1%
a127
 
4.1%
k127
 
4.1%
d127
 
4.1%
Y19
 
0.6%
Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Not asked
838 
Amnestic
122 
Amnestic multiple
115 
Non-amnestic multiple domain
 
10
Non-amnestic single domain
 
6

Length

Max length28
Median length9
Mean length9.99908341
Min length8

Characters and Unicode

Total characters10909
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowNot asked
3rd rowNot asked
4th rowNot asked
5th rowNot asked
ValueCountFrequency (%)
Not asked838
76.8%
Amnestic122
 
11.2%
Amnestic multiple115
 
10.5%
Non-amnestic multiple domain10
 
0.9%
Non-amnestic single domain6
 
0.5%
2021-03-31T16:23:55.256165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:55.341680image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
not838
40.4%
asked838
40.4%
amnestic237
 
11.4%
multiple125
 
6.0%
non-amnestic16
 
0.8%
domain16
 
0.8%
single6
 
0.3%

Most occurring characters

ValueCountFrequency (%)
e1222
11.2%
t1216
11.1%
s1097
10.1%
985
9.0%
o870
8.0%
a870
8.0%
N854
7.8%
d854
7.8%
k838
7.7%
i400
 
3.7%
Other values (9)1703
15.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8817
80.8%
Uppercase Letter1091
 
10.0%
Space Separator985
 
9.0%
Dash Punctuation16
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
e1222
13.9%
t1216
13.8%
s1097
12.4%
o870
9.9%
a870
9.9%
d854
9.7%
k838
9.5%
i400
 
4.5%
m394
 
4.5%
n291
 
3.3%
Other values (5)765
8.7%
ValueCountFrequency (%)
N854
78.3%
A237
 
21.7%
ValueCountFrequency (%)
985
100.0%
ValueCountFrequency (%)
-16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9908
90.8%
Common1001
 
9.2%

Most frequent character per script

ValueCountFrequency (%)
e1222
12.3%
t1216
12.3%
s1097
11.1%
o870
8.8%
a870
8.8%
N854
8.6%
d854
8.6%
k838
8.5%
i400
 
4.0%
m394
 
4.0%
Other values (7)1293
13.1%
ValueCountFrequency (%)
985
98.4%
-16
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII10909
100.0%

Most frequent character per block

ValueCountFrequency (%)
e1222
11.2%
t1216
11.1%
s1097
10.1%
985
9.0%
o870
8.0%
a870
8.0%
N854
7.8%
d854
7.8%
k838
7.7%
i400
 
3.7%
Other values (9)1703
15.6%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
No
948 
Not asked
127 
Yes
 
16

Length

Max length9
Median length2
Mean length2.829514207
Min length2

Characters and Unicode

Total characters3087
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
No948
86.9%
Not asked127
 
11.6%
Yes16
 
1.5%
2021-03-31T16:23:55.536064image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:55.627545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
no948
77.8%
not127
 
10.4%
asked127
 
10.4%
yes16
 
1.3%

Most occurring characters

ValueCountFrequency (%)
N1075
34.8%
o1075
34.8%
s143
 
4.6%
e143
 
4.6%
t127
 
4.1%
127
 
4.1%
a127
 
4.1%
k127
 
4.1%
d127
 
4.1%
Y16
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1869
60.5%
Uppercase Letter1091
35.3%
Space Separator127
 
4.1%

Most frequent character per category

ValueCountFrequency (%)
o1075
57.5%
s143
 
7.7%
e143
 
7.7%
t127
 
6.8%
a127
 
6.8%
k127
 
6.8%
d127
 
6.8%
ValueCountFrequency (%)
N1075
98.5%
Y16
 
1.5%
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2960
95.9%
Common127
 
4.1%

Most frequent character per script

ValueCountFrequency (%)
N1075
36.3%
o1075
36.3%
s143
 
4.8%
e143
 
4.8%
t127
 
4.3%
a127
 
4.3%
k127
 
4.3%
d127
 
4.3%
Y16
 
0.5%
ValueCountFrequency (%)
127
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3087
100.0%

Most frequent character per block

ValueCountFrequency (%)
N1075
34.8%
o1075
34.8%
s143
 
4.6%
e143
 
4.6%
t127
 
4.1%
127
 
4.1%
a127
 
4.1%
k127
 
4.1%
d127
 
4.1%
Y16
 
0.5%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Not asked
601 
Negative
477 
Possible
 
12
Probable
 
1

Length

Max length9
Median length9
Mean length8.550870761
Min length8

Characters and Unicode

Total characters9329
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowNegative
2nd rowNegative
3rd rowNegative
4th rowNegative
5th rowNegative
ValueCountFrequency (%)
Not asked601
55.1%
Negative477
43.7%
Possible12
 
1.1%
Probable1
 
0.1%
2021-03-31T16:23:55.851903image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:55.961779image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
not601
35.5%
asked601
35.5%
negative477
28.2%
possible12
 
0.7%
probable1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e1568
16.8%
a1079
11.6%
N1078
11.6%
t1078
11.6%
s625
 
6.7%
o614
 
6.6%
601
 
6.4%
k601
 
6.4%
d601
 
6.4%
i489
 
5.2%
Other values (6)995
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7637
81.9%
Uppercase Letter1091
 
11.7%
Space Separator601
 
6.4%

Most frequent character per category

ValueCountFrequency (%)
e1568
20.5%
a1079
14.1%
t1078
14.1%
s625
 
8.2%
o614
 
8.0%
k601
 
7.9%
d601
 
7.9%
i489
 
6.4%
g477
 
6.2%
v477
 
6.2%
Other values (3)28
 
0.4%
ValueCountFrequency (%)
N1078
98.8%
P13
 
1.2%
ValueCountFrequency (%)
601
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8728
93.6%
Common601
 
6.4%

Most frequent character per script

ValueCountFrequency (%)
e1568
18.0%
a1079
12.4%
N1078
12.4%
t1078
12.4%
s625
 
7.2%
o614
 
7.0%
k601
 
6.9%
d601
 
6.9%
i489
 
5.6%
g477
 
5.5%
Other values (5)518
 
5.9%
ValueCountFrequency (%)
601
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII9329
100.0%

Most frequent character per block

ValueCountFrequency (%)
e1568
16.8%
a1079
11.6%
N1078
11.6%
t1078
11.6%
s625
 
6.7%
o614
 
6.6%
601
 
6.4%
k601
 
6.4%
d601
 
6.4%
i489
 
5.2%
Other values (6)995
10.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Correct
612 
Not asked
251 
Incorrect
228 

Length

Max length9
Median length7
Mean length7.878093492
Min length7

Characters and Unicode

Total characters8595
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot asked
2nd rowCorrect
3rd rowNot asked
4th rowNot asked
5th rowCorrect
ValueCountFrequency (%)
Correct612
56.1%
Not asked251
23.0%
Incorrect228
 
20.9%
2021-03-31T16:23:56.159218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-03-31T16:23:56.246241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
correct612
45.6%
not251
18.7%
asked251
18.7%
incorrect228
 
17.0%

Most occurring characters

ValueCountFrequency (%)
r1680
19.5%
o1091
12.7%
t1091
12.7%
e1091
12.7%
c1068
12.4%
C612
 
7.1%
N251
 
2.9%
251
 
2.9%
a251
 
2.9%
s251
 
2.9%
Other values (4)958
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7253
84.4%
Uppercase Letter1091
 
12.7%
Space Separator251
 
2.9%

Most frequent character per category

ValueCountFrequency (%)
r1680
23.2%
o1091
15.0%
t1091
15.0%
e1091
15.0%
c1068
14.7%
a251
 
3.5%
s251
 
3.5%
k251
 
3.5%
d251
 
3.5%
n228
 
3.1%
ValueCountFrequency (%)
C612
56.1%
N251
23.0%
I228
 
20.9%
ValueCountFrequency (%)
251
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8344
97.1%
Common251
 
2.9%

Most frequent character per script

ValueCountFrequency (%)
r1680
20.1%
o1091
13.1%
t1091
13.1%
e1091
13.1%
c1068
12.8%
C612
 
7.3%
N251
 
3.0%
a251
 
3.0%
s251
 
3.0%
k251
 
3.0%
Other values (3)707
8.5%
ValueCountFrequency (%)
251
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8595
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1680
19.5%
o1091
12.7%
t1091
12.7%
e1091
12.7%
c1068
12.4%
C612
 
7.1%
N251
 
2.9%
251
 
2.9%
a251
 
2.9%
s251
 
2.9%
Other values (4)958
11.1%

Interactions

2021-03-31T16:23:36.962006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.056509image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.152748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.255384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.353473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.449659image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.543992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.639182image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.730183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.821155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:37.916744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-03-31T16:23:38.010286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2021-03-31T16:23:56.315539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-03-31T16:23:56.455342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-03-31T16:23:56.593501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-03-31T16:23:56.798795image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-03-31T16:23:57.460233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-03-31T16:23:38.315947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-03-31T16:23:40.352267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-03-31T16:23:40.784953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-03-31T16:23:40.962580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

df_indexCOGNITIVE EXAM 162-187: (173) MIME - SCISSORSCOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS_3COGNITIVE EXAM 162-187: HANDEDCOGNITIVE EXAM 162-187: (167) CLOCK DRAWING: TIMECOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: TYPEWRITERCOGNITIVE EXAM 162-187: (184) RECOGNISES OBJECTS: TELEPHONECOGNITIVE EXAM 162-187: (184) RECOGNISES OBJECTS: CUPAge At EpisodeCOGNITIVE EXAM 120-161: (151) REMEMBERS STALINCOGNITIVE EXAM 162-187: (178) RECALLS ADDRESS: WESTCOGNITIVE EXAM 120-161: (143) DEFINES OPINIONCOGNITIVE EXAM 120-161: (132) COMPREHENDS LOOKOPTIMA DIAGNOSES V 2010: AD (NINCDS-ADSDA)OPTIMA DIAGNOSES V 2010: CEREBRO-VASCULAR RISK FACTORSCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: BAROMETERCOGNITIVE EXAM 120-161: (120) IDENTIFIES DAY OF WEEKCOGNITIVE EXAM 120-161: (147) RECOGNISES PICTURES: SHOECOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS 1: APPLEOPTIMA DIAGNOSES V 2010: SMCCOGNITIVE EXAM 120-161: (144) REPETITIONCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: SUITCASECOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS 3: PENNYCOGNITIVE EXAM 120-161: (153) REMEMBERS LINDBERGHOPTIMA DIAGNOSES V 2010: DIAGNOSTIC CODEOPTIMA DIAGNOSES V 2010: VCIOPTIMA DIAGNOSES V 2010: LEWY-BODY DISEASE SEVERITYCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: SHOECOGNITIVE EXAM 120-161: (159) COUNTING BACKWARDSCOGNITIVE EXAM 120-161: (121) IDENTIFIES DATECOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS 2: TABLECOGNITIVE EXAM 162-187: (178) RECALLS ADDRESS: D42COGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: LAMPCOGNITIVE EXAM 120-161: (147) RECOGNISES PICTURES: LAMPOPTIMA DIAGNOSES V 2010: VASCULAR DEMENTIAOPTIMA DIAGNOSES V 2010: DEMENTIA PRESENTOPTIMA DIAGNOSES V 2010: COGNITIVE IMPAIRMENTOPTIMA DIAGNOSES V 2010: CERBRO-VASCULAR DISEASE PRESENTOPTIMA DIAGNOSES V 2010: OTHER SYSTEMIC ILLNESS AFFECTING COGNITIONCOGNITIVE EXAM 120-161: (156) KNOWS PRIME MINISTERCOGNITIVE EXAM 162-187: (185) RECOGNISE PERSONCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: SCALESCOGNITIVE EXAM 120-161: (160) SUBTRACTING SEVENSOPTIMA DIAGNOSES V 2010: MIXED DEMENTIACOGNITIVE EXAM 162-187: (178) RECALLS ADDRESS: BROWNOPTIMA DIAGNOSES V 2010: PARKINSON DISEASEOPTIMA DIAGNOSES V 2010: PETERSEN MCI TYPEOPTIMA DIAGNOSES V 2010: LEWY-BODY DISEASEOPTIMA DIAGNOSES V 2010: PARKINSON DISEASE SEVERITYCOGNITIVE EXAM 162-187: (166) DRAWS HOUSE
0113Not asked3.0Not askedNot askedNot askedNot askedNot asked76.0Not askedNot askedNot askedNot askedNegativeNoNot askedCorrectNot askedCorrectNot askedCorrectNot askedCorrectNot asked0.1Not askedNegativeNot askedNot askedCorrectCorrectNot askedNot askedNot askedNegativeNoYesNot knownNoNot askedNot askedNot asked4.0Not askedNot askedNoNot askedNoNegativeNot asked
1114Correct2.0Not askedCorrectIncorrectCorrectCorrect77.0CorrectCorrectCorrectCorrectNegativeNoIncorrectCorrectCorrectCorrectNot askedIncorrectIncorrectCorrectCorrect0.1Not askedNegativeCorrectCorrectCorrectIncorrectCorrectIncorrectCorrectNegativeNoYesNoneNoCorrectCorrectIncorrect5.0Not askedCorrectNoNot askedNoNegativeCorrect
2116Not asked1.0Not askedNot askedNot askedNot askedNot asked79.0Not askedNot askedNot askedNot askedNegativeYesNot askedCorrectNot askedCorrectNot askedCorrectNot askedIncorrectNot asked0.1Not askedNegativeNot askedNot askedCorrectIncorrectNot askedNot askedNot askedNegativeNoYesNot knownNoNot askedNot askedNot asked5.0Not askedNot askedNoNot askedNoNegativeNot asked
3117Not asked2.0Not askedNot askedNot askedNot askedNot asked80.0Not askedNot askedNot askedNot askedNegativeNoNot askedCorrectNot askedCorrectNot askedCorrectNot askedIncorrectNot asked0.1Not askedNegativeNot askedNot askedCorrectCorrectNot askedNot askedNot askedNegativeNoYesNot knownNoNot askedNot askedNot asked5.0Not askedNot askedNoNot askedNoNegativeNot asked
4118Correct2.0Not askedCorrectIncorrectCorrectCorrect80.0CorrectCorrectCorrectCorrectNegativeNoIncorrectCorrectCorrectCorrectNot askedCorrectIncorrectCorrectCorrect0.1Not askedNegativeCorrectCorrectIncorrectIncorrectCorrectIncorrectCorrectNegativeNoYesNoneNoCorrectCorrectIncorrect5.0Not askedCorrectNoNot askedNoNegativeCorrect
5119Not asked3.0Not askedNot askedNot askedNot askedNot asked81.0Not askedNot askedNot askedNot askedNegativeYesNot askedCorrectNot askedCorrectNot askedCorrectNot askedCorrectNot asked0.1Not askedNegativeNot askedNot askedCorrectCorrectNot askedNot askedNot askedNegativeNoYesNot knownNoNot askedNot askedNot asked5.0Not askedNot askedNoNot askedNoNegativeNot asked
6129Correct3.0Not askedIncorrectCorrectCorrectCorrect85.0CorrectCorrectCorrectCorrectNegativeYesIncorrectCorrectCorrectCorrectYesCorrectIncorrectCorrectCorrect0.2YesNot askedIncorrectCorrectCorrectCorrectCorrectCorrectCorrectNegativeNoYesModerateNoCorrectCorrectIncorrect5.0NoCorrectNoAmnesticNoNot askedCorrect
7130Correct3.0Not askedCorrectCorrectCorrectCorrect85.0CorrectCorrectCorrectCorrectNegativeYesIncorrectCorrectCorrectCorrectYesCorrectIncorrectCorrectCorrect0.2YesNot askedIncorrectCorrectCorrectCorrectCorrectCorrectCorrectNegativeNoYesModerateNoCorrectCorrectCorrect5.0NoCorrectNoAmnesticNoNot askedCorrect
8131Poor3.0RightIncorrectCorrectCorrectCorrect85.0CorrectCorrectCorrectCorrectNegativeYesIncorrectCorrectCorrectCorrectNot askedCorrectIncorrectCorrectCorrect0.2YesNot askedCorrectCorrectIncorrectCorrectCorrectIncorrectCorrectNegativeNoYesModerateNoCorrectCorrectCorrect4.0NoCorrectNoAmnesticNoNot askedCorrect
9132Correct3.0RightCorrectIncorrectCorrectCorrect86.0CorrectCorrectCorrectCorrectNegativeYesIncorrectCorrectCorrectCorrectYesCorrectCorrectCorrectCorrect0.2YesNot askedCorrectCorrectCorrectCorrectCorrectIncorrectCorrectNegativeNoYesModerateNoCorrectCorrectCorrect5.0NoCorrectNoNot askedNoNot askedCorrect

Last rows

df_indexCOGNITIVE EXAM 162-187: (173) MIME - SCISSORSCOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS_3COGNITIVE EXAM 162-187: HANDEDCOGNITIVE EXAM 162-187: (167) CLOCK DRAWING: TIMECOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: TYPEWRITERCOGNITIVE EXAM 162-187: (184) RECOGNISES OBJECTS: TELEPHONECOGNITIVE EXAM 162-187: (184) RECOGNISES OBJECTS: CUPAge At EpisodeCOGNITIVE EXAM 120-161: (151) REMEMBERS STALINCOGNITIVE EXAM 162-187: (178) RECALLS ADDRESS: WESTCOGNITIVE EXAM 120-161: (143) DEFINES OPINIONCOGNITIVE EXAM 120-161: (132) COMPREHENDS LOOKOPTIMA DIAGNOSES V 2010: AD (NINCDS-ADSDA)OPTIMA DIAGNOSES V 2010: CEREBRO-VASCULAR RISK FACTORSCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: BAROMETERCOGNITIVE EXAM 120-161: (120) IDENTIFIES DAY OF WEEKCOGNITIVE EXAM 120-161: (147) RECOGNISES PICTURES: SHOECOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS 1: APPLEOPTIMA DIAGNOSES V 2010: SMCCOGNITIVE EXAM 120-161: (144) REPETITIONCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: SUITCASECOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS 3: PENNYCOGNITIVE EXAM 120-161: (153) REMEMBERS LINDBERGHOPTIMA DIAGNOSES V 2010: DIAGNOSTIC CODEOPTIMA DIAGNOSES V 2010: VCIOPTIMA DIAGNOSES V 2010: LEWY-BODY DISEASE SEVERITYCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: SHOECOGNITIVE EXAM 120-161: (159) COUNTING BACKWARDSCOGNITIVE EXAM 120-161: (121) IDENTIFIES DATECOGNITIVE EXAM 120-161: (161) RECALLS OBJECTS 2: TABLECOGNITIVE EXAM 162-187: (178) RECALLS ADDRESS: D42COGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: LAMPCOGNITIVE EXAM 120-161: (147) RECOGNISES PICTURES: LAMPOPTIMA DIAGNOSES V 2010: VASCULAR DEMENTIAOPTIMA DIAGNOSES V 2010: DEMENTIA PRESENTOPTIMA DIAGNOSES V 2010: COGNITIVE IMPAIRMENTOPTIMA DIAGNOSES V 2010: CERBRO-VASCULAR DISEASE PRESENTOPTIMA DIAGNOSES V 2010: OTHER SYSTEMIC ILLNESS AFFECTING COGNITIONCOGNITIVE EXAM 120-161: (156) KNOWS PRIME MINISTERCOGNITIVE EXAM 162-187: (185) RECOGNISE PERSONCOGNITIVE EXAM 120-161: (146) RECALLS OBJECTS: SCALESCOGNITIVE EXAM 120-161: (160) SUBTRACTING SEVENSOPTIMA DIAGNOSES V 2010: MIXED DEMENTIACOGNITIVE EXAM 162-187: (178) RECALLS ADDRESS: BROWNOPTIMA DIAGNOSES V 2010: PARKINSON DISEASEOPTIMA DIAGNOSES V 2010: PETERSEN MCI TYPEOPTIMA DIAGNOSES V 2010: LEWY-BODY DISEASEOPTIMA DIAGNOSES V 2010: PARKINSON DISEASE SEVERITYCOGNITIVE EXAM 162-187: (166) DRAWS HOUSE
10819554Correct3.0RightIncorrectIncorrectCorrectCorrect79.0CorrectCorrectCorrectCorrectNegativeNoCorrectCorrectCorrectCorrectYesIncorrectCorrectCorrectCorrect0.1NoNot askedIncorrectCorrectCorrectCorrectCorrectCorrectCorrectNegativeNoYesNoneNoCorrectCorrectIncorrect5.0NoCorrectNoNon-amnestic single domainNoNot askedCorrect
10829555Correct3.0RightCorrectIncorrectCorrectCorrect80.0CorrectCorrectCorrectCorrectNegativeNoCorrectCorrectCorrectCorrectYesCorrectIncorrectCorrectCorrect6.0NoNot askedIncorrectOne errorCorrectCorrectCorrectCorrectCorrectNegativeNoNoNoneNoCorrectCorrectIncorrect4.0NoCorrectNoNot askedNoNot askedCorrect
10839556Correct2.0RightCorrectIncorrectCorrectCorrect82.0CorrectCorrectCorrectCorrectNegativeNoIncorrectCorrectCorrectCorrectYesIncorrectIncorrectIncorrectCorrect6.0NoNot askedCorrectOne errorCorrectCorrectCorrectCorrectCorrectNegativeNoNoNoneNoCorrectCorrectCorrect4.0NoCorrectNoNot askedNoNot askedCorrect
10849569Correct1.0LeftIncorrectIncorrectCorrectCorrect63.0CorrectCorrectCorrectCorrectNegativeYesIncorrectCorrectIncorrectIncorrectYesIncorrectIncorrectCorrectCorrect0.2YesNot askedIncorrectOne errorIncorrectIncorrectCorrectIncorrectCorrectNegativeNoYesSevereNoIncorrectCorrectIncorrect3.0NoCorrectNoAmnestic multipleYesNot askedCorrect
10859570Poor2.0Not askedIncorrectIncorrectCorrectCorrect65.0CorrectCorrectCorrectCorrectNegativeYesCorrectCorrectCorrectIncorrectYesIncorrectIncorrectCorrectIncorrect0.2YesNot askedIncorrectCorrectIncorrectCorrectCorrectIncorrectCorrectNegativeNoYesSevereNoIncorrectCorrectIncorrect1.0NoCorrectNoAmnestic multipleYesNot askedCorrect
10869572Poor0.0RightIncorrectIncorrectCorrectCorrect66.0IncorrectIncorrectCorrectIncorrectNegativeNoIncorrectCorrectCorrectIncorrectYesCorrectIncorrectIncorrectIncorrect0.1NoNot askedIncorrectCorrectIncorrectIncorrectIncorrectIncorrectCorrectNegativeNoYesNoneNoIncorrectCorrectIncorrect2.0NoCorrectNoAmnesticNoNot askedCorrect
10879577Poor2.0RightIncorrectIncorrectCorrectCorrect79.0CorrectCorrectCorrectCorrectNegativeNoIncorrectCorrectCorrectCorrectYesCorrectIncorrectIncorrectIncorrect0.1NoNot askedIncorrectCorrectIncorrectCorrectCorrectCorrectCorrectNegativeNoYesMildYesIncorrectCorrectIncorrect3.0NoCorrectNoAmnesticNoNot askedCorrect
10889579Correct2.0RightCorrectIncorrectCorrectCorrect69.0IncorrectIncorrectCorrectCorrectNegativeYesIncorrectIncorrectIncorrectCorrectYesCorrectIncorrectIncorrectCorrect0.1NoNot askedIncorrectCorrectCorrectCorrectCorrectIncorrectIncorrectNegativeNoYesModerateNoCorrectCorrectIncorrect4.0NoIncorrectNoAmnestic multipleNoNot askedCorrect
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